Information output method, information processing device, and processing system

Abstract

The present invention provides an information output method, an information processing device, and a processing system that enable the reduction of the workload on workers associated with the output of abnormal information. [Solution] The system obtains a first measurement value for a first indicator related to the water to be treated at a first timing and a second measurement value for a second indicator related to the water to be treated at a first timing. It then refers to second correspondence information that shows the correspondence between the first measurement value and the second measurement value at a second timing prior to the first timing, and determines whether the relationship between the first correspondence information and the second correspondence information that shows the correspondence between the first measurement value and the second measurement value at the first timing satisfies the first condition. If it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition, it determines whether the attribute related to the measurement of the water to be treated at the first timing satisfies the second condition. If it is determined that the attribute corresponding to the first timing does not satisfy the second condition, it outputs information indicating that the relationship between the first correspondence information and the second correspondence information satisfies the first condition.

Description

Technical Field

[0001] The present disclosure relates to an information output method, an information processing apparatus, and a processing system.

Background Art

[0002] In a processing system (hereinafter also simply referred to as a processing system) that treats water to be treated such as raw water (hereinafter also simply referred to as water to be treated), for example, detection of an abnormality in the water to be treated is performed. In such a processing system, output of information indicating that an abnormality has occurred in the water to be treated (hereinafter also referred to as abnormality information) is controlled in accordance with, for example, the detection status of an abnormality in the water to be treated (see Patent Document 1).

Prior Art Literature

Patent Literature

[0003]

Patent Document 1

Summary of the Invention

Problem to be Solved by the Invention

[0004] Here, when abnormality information is output, an operator of the processing system (hereinafter also simply referred to as an operator) needs to, for example, investigate the abnormality. Specifically, in this case, the operator needs to, for example, investigate whether a chemical substance spill or the like has occurred upstream of the river that is the supply source of the water to be treated. Therefore, in the processing system as described above, it is desired to, for example, reduce the work burden on the operator caused by output of abnormality information.

Means for Solving the Problem

[0005] The information output method in this disclosure obtains a first measurement value for a first indicator related to the water to be treated at a first timing and a second measurement value for a second indicator related to the water to be treated at the first timing, refers to second correspondence information showing the correspondence between the first measurement value and the second measurement value at a second timing prior to the first timing, determines whether the relationship between the first correspondence information showing the correspondence between the first measurement value and the second measurement value at the first timing and the second correspondence information satisfies the first condition, if it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition, determines whether the attribute related to the measurement of the water to be treated at the first timing satisfies the second condition, and outputs information indicating that the relationship between the first correspondence information and the second correspondence information satisfies the first condition. [Effects of the Invention]

[0006] According to the information output method, information processing device, and processing system described herein, it becomes possible to reduce the workload on workers associated with the output of abnormal information. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a diagram illustrating the configuration of the processing system 1000 in the first embodiment. [Figure 2] Figure 2 is a diagram illustrating the configuration of the processing equipment 20 in the first embodiment. [Figure 3] Figure 3 is a diagram illustrating the hardware configuration of the information processing device 1 in the first embodiment. [Figure 4] Figure 4 is a flowchart illustrating the information output process in the first embodiment. [Figure 5] Figure 5 is a flowchart illustrating the information output process in the first embodiment. [Figure 6] Figure 6 illustrates a specific example of the measurement data DT1. [Figure 7] Figure 7 illustrates the information output process in the first embodiment. [Figure 8] Figure 8 is a diagram illustrating the information output process in the first embodiment. [Figure 9] Figure 9 is a diagram illustrating the information output process in the first embodiment. [Figure 10] Figure 10 illustrates a specific example of the measurement data DT1a. [Figure 11] Figure 11 is a diagram illustrating the information output process in the first embodiment. [Modes for carrying out the invention]

[0008] Embodiments of this disclosure will be described below with reference to the drawings. However, this description should not be interpreted as limiting, and will not limit the subject matter described in the claims. Furthermore, various changes, substitutions, and modifications can be made without departing from the spirit and scope of this disclosure. Different embodiments can also be combined as appropriate.

[0009] [Processing system 1000 in the first embodiment] First, we will describe an example of the configuration of the processing system 1000 in the first embodiment. Figure 1 is a diagram illustrating the configuration of the processing system 1000 in the first embodiment. Figure 2 is a diagram illustrating the configuration of the processing equipment 20 in the first embodiment. Note that the locations and number of pumps and piping in the following examples are examples only and are not limited to these.

[0010] The processing system 1000 is, for example, a water purification system including a water purification facility.

[0011] Specifically, the processing system 1000 includes, for example, an information processing system 10 and processing equipment 20.

[0012] The treatment equipment 20 is, for example, a plurality of pieces of equipment that generate treated water (purified water) by performing water purification treatment on water to be treated such as raw water. A specific example of the treatment equipment 20 will be described below.

[0013] [Specific Example of Treatment Equipment 20 in First Embodiment] Figure 2 is a diagram illustrating the treatment equipment 20 in the first embodiment.

[0014] As shown in Figure 2, the treatment equipment 20 includes a plurality of pieces of equipment including, for example, a grit chamber 11, an intake well 12, a mixing basin 13, a flocculation basin 14 (hereinafter also simply referred to as the formation basin 14), a sedimentation basin 15, a filtration basin 16, a purified water basin 17, a distribution reservoir 18, a pump P1, a pump P2, a pump P3, and a storage tank T.

[0015] The grit chamber 11 is, for example, a tank into which water to be treated taken from a river or the like first flows, and is a tank for settling and removing sediment and the like contained in the water to be treated.

[0016] The pump P1 is, for example, a pump provided in a pipe communicating the grit chamber 11 and the intake well 12. Specifically, the pump P1 supplies, for example, the water to be treated stored in the grit chamber 11 to the intake well 12.

[0017] The intake well 12 is, for example, a tank that adjusts the supply amount of the water to be treated supplied from the grit chamber 11 and supplies the adjusted water to the mixing basin 13.

[0018] The mixing basin 13 is, for example, a tank that injects a coagulant into the water to be treated supplied from the intake well 12.

[0019] The flocculation basin 14 is, for example, a tank that forms flocs by stirring the water to be treated supplied from the mixing basin 13, thereby causing suspended substances contained in the water to be treated supplied from the mixing basin 13 to coagulate via the coagulant.

[0020] The sedimentation basin 15 is, for example, a tank that settles flocs contained in the water to be treated supplied from the flocculation basin 14 and separates the flocs from the water to be treated.

[0021] The filtration tank 16 is a tank that filters the water to be treated supplied from the sedimentation tank 15 by using a filter body (not shown) made of, for example, sand or gravel.

[0022] The water purification reservoir 17 is a tank that temporarily stores the water to be treated supplied from the filtration tank 16 (for example, the water to be treated after chlorine disinfection has been performed downstream of the filtration tank 16) and supplies it to the distribution reservoir 18.

[0023] Pump P2 is, for example, a pump installed in a pipe connecting the water purification reservoir 17 and the water distribution reservoir 18. Specifically, pump P2 supplies, for example, the treated water stored in the water purification reservoir 17 to the water distribution reservoir 18.

[0024] The water distribution reservoir 18 temporarily stores the treated water supplied from the water purification reservoir 17 and supplies it to households, etc. (not shown).

[0025] Storage tank T is, for example, a tank for storing a coagulant to be injected into the water to be treated.

[0026] Pump P3 is, for example, a pump installed in the piping connecting the storage tank T and the mixing tank 13. Specifically, pump P3 supplies the mixing tank 13 with a coagulant corresponding to an injection rate predetermined by, for example, the administrator of the treatment system 1000 (hereinafter also simply referred to as the administrator).

[0027] Furthermore, the treatment equipment 20 may include, for example, other pumps (not shown) besides pumps P1, P2, and P3. Also, the treatment equipment 20 may supply chemicals other than coagulants (for example, caustic soda, etc.) to the water to be treated.

[0028] Returning to Figure 1, the information processing system 10 includes, for example, an information processing device 1 and an operation terminal 2.

[0029] The operating terminal 2 is, for example, one or more PCs (Personal Computers) or mobile devices such as smartphones, and is a terminal on which the worker inputs necessary information to the information processing device 1.

[0030] The information processing device 1 is, for example, a physical machine or a virtual machine, and by monitoring the water to be treated (water taken from a river, etc.) that flows into the processing equipment 20, it detects any abnormalities (for example, abnormalities in water quality) occurring in the water to be treated and performs processing (hereinafter also simply referred to as information output processing) to output information indicating the detected abnormality (abnormality information).

[0031] Specifically, the information processing device 1 acquires, for example, a measured value (hereinafter also called the first measured value) for an indicator (hereinafter also called the first indicator) related to the water to be treated at a predetermined timing (hereinafter also called the first timing). The information processing device 1 also acquires, for example, a measured value (hereinafter also called the second measured value) for an indicator (hereinafter also called the second indicator) related to the water to be treated at the first timing that is different from the first indicator. The first indicator is, for example, the chlorine demand in the water to be treated. The first measured value in this case is, for example, a measured value taken by a measuring device (not shown) installed in the sedimentation basin 11, and is a measured value for the chlorine demand in the water to be treated that flows into the sedimentation basin 11. The second indicator is, for example, the ammonia concentration in the water to be treated. The second measured value in this case is, for example, a measured value taken by a measuring device (not shown) installed in the sedimentation basin 11, and is a measured value for the ammonia concentration in the water to be treated that flows into the sedimentation basin 11. Furthermore, the measuring devices used to measure the first and second measurement values ​​may be installed, for example, in the upstream facilities of the sedimentation basin 11 (e.g., the water intake), the water intake well 12, or the inlet of the water to be treated in the mixing basin 13.

[0032] Next, the information processing device 1 in this embodiment refers to a storage unit 130 that stores correspondence information (hereinafter also referred to as second correspondence information) showing the correspondence between the first measurement value and the second measurement value at a timing prior to the first timing (hereinafter also referred to as the second timing), and determines whether the relationship between the correspondence information (hereinafter also referred to as first correspondence information) showing the correspondence between the first measurement value and the second measurement value at the first timing (hereinafter also referred to as first correspondence information) and the second correspondence information satisfies the first condition. The first condition is, for example, that the degree of deviation of the first correspondence information with respect to the second correspondence information (hereinafter also simply referred to as the degree of deviation) satisfies a predetermined condition. Specifically, the first condition is, for example, that the degree of deviation is greater than or equal to a predetermined threshold (hereinafter also referred to as a predetermined threshold).

[0033] As a result, if it is determined that the relationship between the first corresponding information and the second corresponding information satisfies the first condition, the information processing device 1 in this embodiment determines, for example, whether the attributes related to the measurement of the water to be treated at the first timing satisfy the second condition. The attributes related to the measurement of the water to be treated at the first timing are, for example, the turbidity of the water to be treated, the chromaticity of the water to be treated, the ultraviolet absorbance (E260) of the water to be treated, or the organic carbon concentration (TOC: Total Organic Carbon) of the water to be treated at the first timing (hereinafter, these are collectively referred to simply as turbidity, etc.). The second condition in this case is, for example, that the turbidity, etc. of the water to be treated at the first timing satisfies a predetermined condition. Specifically, the second condition in this case is, for example, that the turbidity, etc. of the water to be treated at the first timing is above a predetermined threshold. The attributes related to the measurement of the water to be treated at the first timing are, for example, the fluctuation status of at least one of the first measurement value and the second measurement value within a predetermined time before and after the first timing (hereinafter, also simply referred to as fluctuation status). The second condition, in this case, is that the fluctuations of the treated water corresponding to the first timing satisfy predetermined conditions. Specifically, the second condition, in this case, is that the fluctuation range of at least one of the first and second measured values ​​within a predetermined time period before and after the first timing is greater than or equal to a predetermined threshold. The second condition, in this case, is that at least one of the first and second measured values ​​within a predetermined time period before and after the first timing remains within or constant within a predetermined range (within a predetermined range of abnormal values).

[0034] Subsequently, if the information processing device 1 in this embodiment determines, for example, that the attribute corresponding to the first timing does not satisfy the second condition, it outputs information (abnormal information) indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition.

[0035] In other words, for example, if the first correspondence information (the value indicated by the first correspondence information) showing the correspondence between the newly measured first measurement value and the second measurement value deviates from the second correspondence information (the value indicated by the second correspondence information) stored in the storage unit 130, it is possible to determine, for example, that an abnormality may have occurred at the measurement timing of the first and second measurement values. Furthermore, even if it is possible to determine that an abnormality may have occurred at the measurement timing of the first and second measurement values, if the cause of the abnormality can be identified, it is possible to determine that an investigation by an operator is unnecessary.

[0036] Therefore, the administrator pre-selects, for example, a combination of a first indicator and a second indicator related to the treated water that can be determined to be correlated with each other (for example, a combination of chlorine demand and ammonia concentration), and repeatedly measures the combination of first and second measured values ​​corresponding to each of the selected first and second indicators and stores (accumulates) them in the storage unit 130. Then, the administrator generates, for example, second correspondence information showing the correspondence between the first and second measured values ​​in each accumulated combination and stores it in the storage unit 130. Specifically, the administrator generates, for example, a regression line (mathematical formula of the regression line) for each point when plotting each point representing the accumulated combination of first and second measured values ​​on a two-dimensional plane where the first and second measured values ​​correspond to the vertical and horizontal axes, respectively, as the second correspondence information.

[0037] Subsequently, if the information processing device 1 acquires newly measured first and second measurement values, it compares the first correspondence information, which shows the correspondence between the acquired first and second measurement values, with the second correspondence information stored in the storage unit 130 to determine whether the first correspondence information deviates from the second correspondence information. Specifically, the information processing device 1 determines whether the distance from a point representing the combination of the newly measured first and second measurement values ​​to the second correspondence information (regression line), when the first and second measurement values ​​are plotted on a two-dimensional plane where the vertical and horizontal axes correspond to each other, is greater than or equal to a predetermined threshold.

[0038] As a result, if the first corresponding information is determined to deviate from the second corresponding information, the information processing device 1 determines, for example, whether the turbidity of the water to be treated at the measurement timing (first timing) of the newly measured first and second measurements is above a predetermined threshold. The information processing device 1 then outputs abnormal information only if it determines, for example, that the turbidity of the water to be treated is not above a predetermined threshold, and prompts the operator to conduct an investigation into the cause of the deviation exceeding a predetermined threshold. On the other hand, if the information processing device 1 determines, for example, that the turbidity of the water to be treated is above a predetermined threshold, it does not output abnormal information.

[0039] As a result, the information processing device 1 in this embodiment can suppress the frequency of outputting abnormal information. Specifically, the information processing device 1 in this embodiment can suppress the frequency of outputting abnormal information by determining whether or not an investigation by a worker or external organization is necessary when an abnormality is detected. Therefore, the information processing device 1 in this embodiment can suppress the frequency of workers or external organizations conducting investigations into abnormalities (for example, investigations into whether or not chemical substances are leaking upstream of the river that supplies the treated water). Consequently, the information processing device 1 in this embodiment can reduce the workload of workers.

[0040] The following explanation will focus on the case where the combination of the first and second indicators is chlorine demand and ammonia concentration, but is not limited to this. Specifically, the first and second indicators may be, for example, pH, alkalinity, electrical conductivity (EC), oxidation-reduction potential (ORP), dissolved oxygen (DO), organic carbon, or fluorescence intensity.

[0041] Furthermore, the information processing device 1 in this embodiment may, for example, output information (hereinafter also referred to as alarm information) indicating that, when it is determined that the attribute corresponding to the first timing satisfies the second condition, the relationship between the first corresponding information and the second corresponding information satisfies the first condition, and the attribute corresponding to the first timing satisfies the second condition. The alarm information includes, for example, information indicating that an abnormality may have occurred at the measurement timing of the first and second measured values, but that the cause of the abnormality can be identified (explained). The alarm information also includes, for example, information indicating the content and type of the cause of the abnormality (identified cause).

[0042] Furthermore, the following description will assume that the processing system 1000 (information processing system 10) has one information processing device 1, but it is not limited to this. Specifically, the processing system 1000 may have, for example, multiple information processing devices 1. And the information output processing may be performed in a distributed manner across multiple information processing devices 1.

[0043] [Hardware configuration of the information processing system 10 in the first embodiment] Next, the hardware configuration of the information processing system 10 in the first embodiment will be described. Figure 3 is a diagram illustrating the hardware configuration of the information processing device 1 in the first embodiment.

[0044] As shown in Figure 3, the information processing device 1 includes a processor (CPU 101), a memory 102, a communication device 103, a storage medium 104, and an output device 105. Each part is connected to the others via a bus 106.

[0045] The storage medium 104 has, for example, a program storage area (not shown) for storing a program 110 for performing information output processing. The storage medium 104 also has, for example, a storage unit 130 (hereinafter also referred to as the information storage area 130) for storing information used when performing information output processing. The storage medium 104 may be, for example, an HDD (Hard Disk Drive) or an SSD (Solid State Drive).

[0046] The CPU 101 performs information output processing, for example, by executing a program 110 loaded into memory 102 from storage medium 104.

[0047] The communication device 103 accesses the processing equipment 20 and the operation terminal 2 via a network NW, such as the Internet.

[0048] The output device 105 is, for example, a display, which outputs the processing results of the information output processing performed by the CPU 101.

[0049] The electronic circuitry of the information processing device 1 may be, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). In this case, the information output processing may be performed, for example, on the FPGA or ASIC.

[0050] [Information output processing in the first embodiment] Next, the information output processing in the first embodiment will be described. Figures 4 and 5 are flowcharts illustrating the information output processing in the first embodiment. Figures 6 to 11 are diagrams illustrating the information output processing in the first embodiment. The following description will assume that the information output processing is performed by the information processing device 1, but the information output processing may also be performed manually by, for example, an administrator or worker.

[0051] [Information generation process] First, we will explain the process of generating the second corresponding information (hereinafter also referred to as the information generation process) within the information output process.

[0052] The information processing device 1 acquires, for example, a combination of a first measurement value and a second measurement value measured at a second timing from each measuring device (not shown) installed in the processing equipment 20 (step S1 in Figure 4). The information processing device 1 then stores, for example, the acquired combination of the first measurement value and the second measurement value in the information storage area 130.

[0053] Specifically, the information processing device 1, for example, accesses each measuring device and acquires combinations of first and second measurement values ​​measured at each of multiple timings (multiple second timings). Then, the information processing device 1 generates measurement data DT1, which includes each of the acquired combinations of first and second measurement values, and stores it in the information storage area 130.

[0054] The first and second measurement values ​​may be automatically transmitted from each measuring device to the information processing device 1, for example. The information processing device 1 may then generate measurement data DT1, which includes the combination of the first and second measurement values ​​transmitted from each measuring device, and store it in the information storage area 130.

[0055] Furthermore, the information processing device 1 may, for example, acquire measurement values ​​(hereinafter simply referred to as "other measurement values") from each measuring device in step S1, in addition to the first and second measurement values, for other indicators different from the first and second indicators (hereinafter simply referred to as "other indicators"). The information processing device 1 may then generate measurement data DT1 that includes the other measurement values. A specific example of the measurement data DT1 will be described below.

[0056] [Specific example of measurement data DT1] Figure 6 illustrates a specific example of measurement data DT1. In the following explanation, we will assume that in step S1, a measurement value for chlorine demand is taken as the first measurement value, a measurement value for ammonia concentration is taken as the second measurement value, and a measurement value for turbidity of the treated water is obtained as another measurement value for another indicator. Furthermore, in the following explanation, we will assume that measurement data DT1 is generated, which includes the measurement value for chlorine demand (first measurement value), the measurement value for ammonia concentration (second measurement value), and the measurement value for turbidity (other measurement value).

[0057] The measurement data DT1 shown in Figure 6 includes the following items: "Date and Time," which sets the date and time when each measurement was acquired; "Chlorine Demand," which sets the measured value (first measurement value) for the chlorine demand (first indicator) in the treated water measured at each date and time; "Ammonia Concentration," which sets the measured value (second measurement value) for the ammonia concentration (second indicator) in the treated water measured at each date and time; and "Turbidity," which sets the measured value (other measurement value) for the turbidity (other indicator) of the treated water measured at each date and time. Note that the turbidity of the treated water may be measured by a measuring device (not shown) installed in the sedimentation tank 11, for example.

[0058] Specifically, in the first row of the measurement data DT1 shown in Figure 6, for example, "Date and Time" is set to "02 / 01 12:00", "Chlorine Demand" is set to "2 (mg / L)", "Ammonia Concentration" is set to "0.3 (mg / L)", and "Turbidity" is set to "14 (degrees)".

[0059] Furthermore, in the second row of the measurement data DT1 shown in Figure 6, for example, "Date and Time" is set to "02 / 01 13:00", "Chlorine Demand" is set to "3 (mg / L)", "Ammonia Concentration" is set to "0.2 (mg / L)", and "Turbidity" is set to "12 (degrees)". Explanations of the other data included in Figure 6 are omitted.

[0060] Returning to Figure 4, the information processing device 1 generates, for example, second correspondence information showing the correspondence between the first measurement value and the second measurement value acquired in step S1 (step S2 in Figure 4). Then, the information processing device 1 stores the generated second correspondence information in the information storage area 130.

[0061] Specifically, as shown in graph G1 of Figure 7, the information processing device 1 plots each point Pa representing each combination of chlorine demand and ammonia concentration contained in the measurement data DT1 on a two-dimensional plane where, for example, chlorine demand and ammonia concentration correspond to the vertical and horizontal axes, respectively, and generates a regression line L1 for each plotted point Pa as second corresponding information. The information processing device 1 then stores the generated regression line L1 (the formula for the regression line L1) in the information storage area 130. Note that the regression line L1 shown in the example in Figure 7 is a straight line with a slope of 5.89 and a Y-intercept of 1.22.

[0062] Then, the information processing device 1 calculates a predetermined threshold using, for example, the first and second measurement values ​​obtained in step S1 and the second corresponding information generated in step S2 (step S3 in Figure 4). The information processing device 1 then stores the calculated predetermined threshold in the information storage area 130.

[0063] Specifically, as shown in graph G1 of Figure 7, the information processing device 1 calculates, for example, the deviation (hereinafter also simply called the regression residual R1) between the chlorine demand corresponding to each point Pa and the regression line L1 for each point Pa. Then, as shown in graph G2 of Figure 8, the information processing device 1 generates a frequency distribution of the calculated regression residual R1. Furthermore, the information processing device 1 calculates, for example, the feature quantities (e.g., the standard deviation) of the distribution of the regression residual R1.

[0064] Furthermore, as shown in graph G3 of Figure 9, when the information processing device 1 evaluates the similarity (fit) between the distribution of the regression residual R1 and the normal distribution using a normal QQ plot (Quantile-Quantile plot), it forms an almost straight line when the value of the regression residual R1 is less than 1.7, while it does not form a straight line when the value of the regression residual R1 is greater than 1.7. Therefore, it is possible to identify points Pa where the regression residual R1 from the regression line L1 is 1.7 or greater as so-called outliers. In other words, it is possible to determine that points Pa where the regression residual R1 from the regression line L1 is 1.7 or greater are points where, for example, there is a high probability that an anomaly occurred at the measurement timing of the first and second measurement values ​​corresponding to that point Pa. Note that the vertical and horizontal axes in graph G3 shown in Figure 9 correspond to the regression residual R1 and the theoretical value of the normal distribution (the standardized value of the expected value of the regression residual R1), respectively.

[0065] Therefore, in this case, the information processing device 1 identifies, for example, 1.7 as a predetermined threshold in step S3.

[0066] [Main process] Next, we will explain the main process of the information output process (hereinafter also referred to as the main process).

[0067] The information processing device 1 acquires, for example, a combination of a first measurement value and a second measurement value measured at a first timing (a new combination of a first measurement value and a second measurement value) from each measuring device (not shown) installed in the processing equipment 20 (step S11 in Figure 5). The information processing device 1 then stores the acquired combination of a first measurement value and a second measurement value in the information storage area 130.

[0068] Specifically, the information processing device 1, for example, accesses each measuring device and acquires a combination of a first measurement value and a second measurement value measured at a first timing. Then, the information processing device 1 generates measurement data DT1 (hereinafter also referred to as measurement data DT1a) including the acquired combination of the first measurement value and the second measurement value and stores it in the information storage area 130.

[0069] The first and second measurement values ​​may be automatically transmitted from each measuring device to the information processing device 1, for example. The information processing device 1 may then generate measurement data DT1a, which includes the combination of the first and second measurement values ​​transmitted from each measuring device, and store it in the information storage area 130.

[0070] Furthermore, the information processing device 1 may, for example, acquire other measurement values ​​from each measuring device in step S11, in addition to the first and second measurement values. The information processing device 1 may then generate measurement data DT1a that includes the other measurement values. A specific example of the measurement data DT1a will be described below.

[0071] [Specific example of measurement data DT1a] Figure 10 illustrates a specific example of measurement data DT1a. In the following explanation, it is assumed that the turbidity of the treated water measured at the first timing in step S11 is acquired and that this turbidity is included in the measurement data DT1a.

[0072] The measurement data DT1a shown in Figure 10 has the same items as the measurement data DT1 described in Figure 6, for example.

[0073] Specifically, the measurement data DT1a shown in Figure 10 includes, for example, "Date and Time" set to "02 / 01 12:00", "Chlorine Demand" set to "14 (mg / L)", "Ammonia Concentration" set to "0.8 (mg / L)", and "Turbidity" set to "120 (degrees)".

[0074] Returning to Figure 5, the information processing device 1 determines, for example, whether the degree of discrepancy between the first correspondence information, which shows the correspondence between the first measurement value and the second measurement value acquired in step S11, and the second correspondence information generated in step S2 (information generation process), exceeds a predetermined threshold (step S12 in Figure 5).

[0075] Specifically, as shown in graph G4 of Figure 11, the information processing device 1 plots points Pb representing combinations of chlorine demand and ammonia concentration contained in the measurement data DT1a on a two-dimensional plane where, for example, chlorine demand and ammonia concentration correspond to the vertical and horizontal axes, respectively. Furthermore, as shown in graph G4 of Figure 11, the information processing device 1 identifies a line L2 whose slope is the same as the regression line L1 and whose Y-intercept is 1.7 greater than the regression line L1, for example, if the predetermined threshold calculated in step S3 (information generation process) is 1.7.

[0076] Then, as shown in Figure 11, if point Pb is plotted above the line L2, for example, the information processing device 1 determines that the degree of discrepancy between the first corresponding information and the second corresponding information exceeds a predetermined threshold. In other words, in this case, the information processing device 1 determines that there is a high probability that an abnormality occurred at the measurement timing of the first and second measured values ​​corresponding to point Pb.

[0077] On the other hand, if, for example, point Pb is not plotted above the line L2, that is, if point Pb is plotted below the line L2 or if point Pb is plotted on the line L2, the information processing device 1 determines that the degree of discrepancy between the first corresponding information and the second corresponding information does not exceed a predetermined threshold. In other words, in this case, the information processing device 1 determines that, for example, there is little possibility that an abnormality occurred at the measurement timing of the first and second measured values ​​corresponding to point Pb.

[0078] In this case, the information processing device 1 may, for example, determine whether the deviation (regression residual) between the chlorine demand corresponding to point Pb and the regression line L1 is 1.7 or greater. If, for example, the information processing device 1 determines that the deviation (regression residual) between point Pb and line L1 is 1.7 or greater, the information processing device 1 may determine that the degree of discrepancy between the first corresponding information and the second corresponding information exceeds a predetermined threshold.

[0079] As a result, if the information processing device 1 determines that the degree of discrepancy between the first correspondence information showing the correspondence between the first and second measured values ​​obtained in step S11 and the second correspondence information generated in step S2 exceeds a predetermined threshold, the information processing device 1 determines, for example, whether the cause of the discrepancy exceeding the predetermined threshold can be identified (explained) (YES in step S12 of Figure 5, step S13 of Figure 5).

[0080] Specifically, if the information processing device 1 determines, for example, that the turbidity contained in the measurement data DT1a satisfies the conditions, it determines that the cause of the deviation exceeding a predetermined threshold can be identified. More specifically, if the information processing device 1 determines, for example, that the turbidity contained in the measurement data DT1a is above a predetermined threshold (hereinafter also referred to as a specific threshold), it determines that the cause of the deviation exceeding a predetermined threshold can be identified.

[0081] In other words, when the turbidity of the treated water is higher than normal, it is possible to determine, for example, that this is likely causing the deviation to exceed a predetermined threshold. Therefore, in this case, the information processing device 1 determines that, for example, the cause of the deviation exceeding the predetermined threshold has already been identified.

[0082] Furthermore, the information processing device 1 determines, for example, that if it determines that the fluctuation status of at least one of the first and second measured values ​​measured within a predetermined time before and after the measurement timing (first timing) of the measurement data DT1a satisfies a condition, it determines that the cause of the deviation exceeding a predetermined threshold can be identified. More specifically, the information processing device 1 determines, for example, that if the fluctuation status of at least one of the first and second measured values ​​measured within a predetermined time before the measurement timing of the measurement data DT1a, within a predetermined time after the measurement timing of the measurement data DT1a, or within a predetermined time spanning the measurement timing of the measurement data DT1a, matches a predetermined fluctuation status (hereinafter also referred to as the predetermined fluctuation status), it determines that the cause of the deviation exceeding a predetermined threshold can be identified. The predetermined fluctuation status is a situation in which the fluctuation range of at least one of the first and second measured values ​​is greater than or equal to a predetermined threshold. Furthermore, the predetermined fluctuation conditions in this case refer to a situation where, for example, at least one of the first measurement value and the second measurement value is moving within a predetermined range (within a predetermined range of abnormal values) or remains constant.

[0083] In other words, if at least one of the first measurement value and the second measurement value fluctuates wildly at the timing before and after the measurement timing of the measurement data DT1a, it is possible to determine, for example, that this is likely causing the deviation to exceed a predetermined threshold. Therefore, in this case, the information processing device 1 determines that, for example, the cause of the deviation exceeding the predetermined threshold has already been identified.

[0084] Furthermore, the specific threshold may be determined, for example, according to the measured value (first measured value) of chlorine demand included in the measurement data DT1a. Specifically, the specific threshold may be a threshold that increases as the measured value of chlorine demand included in the measurement data DT1a increases, and decreases as the measured value of chlorine demand included in the measurement data DT1a decreases. Alternatively, the specific threshold may be determined, for example, according to the regression residual R1 corresponding to point Pb (the regression residual R1 between the chlorine demand corresponding to point Pb and the regression line L1). Specifically, the specific threshold may be a threshold that increases as the regression residual R1 corresponding to point Pb increases, and decreases as the regression residual R1 corresponding to point Pb decreases.

[0085] Furthermore, the information processing device 1 may determine, for example, that in step S11, measured values ​​(other measured values) for ultraviolet absorbance (other indicators) of the water to be treated are acquired, and measurement data DT1a including the acquired measured values ​​for turbidity are generated. In this case, if the information processing device 1 determines that the deviation (hereinafter also referred to as a specific value) between the predicted chlorine demand calculated using the measured values ​​for turbidity and ultraviolet absorbance included in the measurement data DT1a and the regression line L1 satisfies a condition, then the device may determine that the cause of the deviation exceeding a predetermined threshold can be identified. The specific value may, for example, be the sum of a value calculated by multiplying the measured values ​​for turbidity included in the measurement data DT1a by a predetermined other coefficient and a value calculated by multiplying the measured values ​​for ultraviolet absorbance included in the measurement data DT1a by a predetermined coefficient. Specifically, the information processing device 1 may determine, for example, that if the specific value is less than a predetermined threshold, the device can determine that the cause of the deviation exceeding a predetermined threshold can be identified.

[0086] Returning to Figure 5, if it is determined that the cause of the deviation exceeding a predetermined threshold cannot be identified, the information processing device 1 outputs abnormal information to the operation terminal 2, for example (NO in step S13 of Figure 5, step S14 of Figure 5).

[0087] In other words, a situation where the cause of the deviation exceeding a predetermined threshold cannot be identified is, for example, when it is determined that the worker or an external organization needs to conduct an investigation into the abnormality (for example, an investigation into whether or not chemical substances are leaking upstream of the river that supplies the treated water). Therefore, in this case, for example, the information processing device 1 outputs abnormality information to prompt the worker to conduct an investigation into the cause of the deviation exceeding a predetermined threshold.

[0088] On the other hand, if the information processing device 1 determines that the degree of deviation between the first correspondence information, which shows the correspondence between the first and second measured values ​​obtained in step S11, and the second correspondence information generated in step S2 does not exceed a predetermined threshold, the information processing device 1 does not output abnormal information, for example (NO in step S12 of Figure 5). Similarly, if the information processing device 1 determines that the cause of the deviation exceeding a predetermined threshold can be identified, for example, the information processing device 1 does not output abnormal information (YES in step S13 of Figure 5).

[0089] Thus, the information processing device 1 in this embodiment acquires, for example, a first measurement value for a first indicator related to the water to be treated at a first timing. The information processing device 1 in this embodiment also acquires, for example, a second measurement value for a second indicator related to the water to be treated at a first timing. Subsequently, the information processing device 1 in this embodiment refers to, for example, a storage unit 130 that stores second correspondence information showing the correspondence between the first measurement value and the second measurement value at a second timing, and determines whether the relationship between the first correspondence information showing the correspondence between the first measurement value and the second measurement value at the first timing and the second correspondence information satisfies the first condition.

[0090] As a result, if it is determined that the relationship between the first corresponding information and the second corresponding information satisfies the first condition, the information processing device 1 in this embodiment determines, for example, whether the attribute related to the measurement of the water to be treated at the first timing satisfies the second condition. If the information processing device 1 in this embodiment determines, for example, that the attribute corresponding to the first timing does not satisfy the second condition, it outputs information (abnormal information) indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition.

[0091] Specifically, the information processing device 1 in this embodiment, for example, refers to the second correspondence information and determines that the degree of deviation of the first correspondence information from the second correspondence information satisfies a condition (hereinafter also referred to as other conditions), and then determines that the relationship between the first correspondence information and the second correspondence information satisfies the first condition.

[0092] Furthermore, the information processing device 1 in this embodiment acquires, for example, other measured values ​​for other indicators related to the treated water at the first timing. Then, if, for example, the other measured values ​​satisfy a condition (hereinafter also referred to as "other conditions"), the information processing device 1 in this embodiment determines that the attribute corresponding to the first timing satisfies the second condition.

[0093] Furthermore, in this embodiment, the information processing device 1 determines that the attribute corresponding to the first timing satisfies the second condition if, for example, the fluctuation status of at least one of the first measurement value and the second measurement value within a predetermined time period before and after the first timing satisfies a condition (hereinafter also referred to as the other condition).

[0094] Furthermore, in this embodiment, if the information processing device 1 determines, for example, that the attribute corresponding to the first timing satisfies the second condition, it outputs information (alarm information) indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition, and that the attribute corresponding to the first timing satisfies the second condition.

[0095] As a result, the information processing device 1 in this embodiment can suppress the frequency of outputting abnormal information. Specifically, the information processing device 1 in this embodiment can suppress the frequency of outputting abnormal information by determining whether or not an investigation by a worker or external organization is necessary when an abnormality is detected. Therefore, the information processing device 1 in this embodiment can suppress the frequency of workers or external organizations conducting investigations into abnormalities (for example, investigations into whether or not chemical substances are leaking upstream of the river that supplies the treated water). Consequently, the information processing device 1 in this embodiment can reduce the workload of workers.

[0096] Furthermore, the information processing device 1 in this embodiment can, for example, output alarm information in addition to abnormal information, thereby enabling the operator to recognize abnormalities that may have occurred at the measurement timing of the first and second measurement values, even if abnormal information was not output.

[0097] In the above example, we have described the case where the information processing device 1 calculates the regression line L1 (the formula for the regression line L1) as the second correspondence information, but this is not the only case. Specifically, the information processing device 1 may, for example, generate a learned learning model (hereinafter simply referred to as the learning model) as the second correspondence information in the information generation process. Then, the information processing device 1 may, for example, use the learning model in the main process to determine whether the first correspondence information is an outlier or not.

[0098] More specifically, the information processing device 1 may generate a learning model by learning (e.g., unsupervised learning) on ​​training data that includes information indicating the correspondence between the first and second measured values ​​measured at a second timing (e.g., coordinates indicating the correspondence between the first and second measured values ​​on a two-dimensional plane). The information processing device 1 may then, for example, input first correspondence information (e.g., coordinates indicating the correspondence between the first and second measured values ​​on a two-dimensional plane) and refer to the information output from the learning model to determine whether the first correspondence information is an outlier (whether the information output from the learning model indicates an outlier). If the information processing device 1 determines that the first correspondence information is an outlier, it may, for example, determine that the relationship between the first correspondence information and the second correspondence information satisfies the first condition.

[0099] [First variation] Next, a modified example of the information output processing in the first embodiment (hereinafter also referred to as the first modified example) will be described.

[0100] The information processing device 1 may, for example, in the information generation process (steps S1 to S3 in Figure 4), generate not only second correspondence information showing the correspondence between the first measurement value and the second measurement value and a predetermined threshold (hereinafter also referred to as the first threshold), but also other correspondence information showing the correspondence between the first measurement value and other measurement values ​​(hereinafter also referred to as the third measurement value) (hereinafter also referred to as the fourth correspondence information) and other predetermined thresholds (hereinafter also referred to as the second threshold).

[0101] Furthermore, the information processing device 1 may, for example, in step S12, make a determination as to whether the relationship between the first correspondence information and the second correspondence information, which shows the correspondence between the first measurement value and the second measurement value at the first timing, satisfies the first condition, and make a determination as to whether the relationship between the correspondence information (hereinafter also referred to as the third correspondence information) and the fourth correspondence information, which shows the correspondence between the first measurement value and the third measurement value at the first timing, satisfies the condition (hereinafter also referred to as the third condition). In addition, the information processing device 1 may, for example, in step S13, make a determination as to whether the attribute corresponding to the first timing satisfies the second condition if the relationship between the first correspondence information and the second correspondence information satisfies the first condition and the relationship between the third correspondence information and the fourth correspondence information satisfies the third condition.

[0102] Specifically, the information processing device 1 may, for example, in step S12, perform a determination of whether the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and a determination of whether the degree of deviation of the third corresponding information to the fourth corresponding information is greater than or equal to a second threshold. Furthermore, the information processing device 1 may, for example, in step S13, if the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and the degree of deviation of the third corresponding information to the fourth corresponding information is greater than or equal to a second threshold, perform a determination of whether the cause of the deviation of the first corresponding information to the second corresponding information being greater than or equal to a first threshold can be identified.

[0103] Furthermore, the information processing device 1 may, for example, in step S13, determine whether the attribute corresponding to the first timing satisfies the second condition if at least the relationship between the first corresponding information and the second corresponding information satisfies the first condition, or if at least the relationship between the third corresponding information and the fourth corresponding information satisfies the third condition.

[0104] Specifically, the information processing device 1 may, for example, in step S13, determine whether the cause of the deviation of the first corresponding information from the second corresponding information being greater than or equal to the first threshold is identifiable if at least the deviation of the third corresponding information from the fourth corresponding information is greater than or equal to the second threshold.

[0105] Furthermore, if the information processing device 1 determines, for example, that the relationship between the first corresponding information and the second corresponding information satisfies the first condition and the attribute corresponding to the first timing does not satisfy the second condition (YES in step S12 of Figure 5, NO in step S13 of Figure 5), then in step S14, it may further determine whether the relationship between the third corresponding information and the fourth corresponding information satisfies the third condition, and if it determines that the relationship between the third corresponding information and the fourth corresponding information satisfies the third condition, it may output abnormal information.

[0106] Specifically, if the information processing device 1 determines, for example, that the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and that the cause of the deviation of the first corresponding information to the second corresponding information being greater than or equal to the first threshold can be identified, then in step S14, it may further determine whether the degree of deviation of the third corresponding information to the fourth corresponding information is greater than or equal to a second threshold, and if the degree of deviation of the third corresponding information to the fourth corresponding information is greater than or equal to the second threshold, it may output abnormal information.

[0107] [Second variation] Next, we will describe another variation of the information output process in the first embodiment (hereinafter also referred to as the second variation).

[0108] The information processing device 1 may, for example, in the information generation process (steps S1 to S3 in Figure 4), generate not only second correspondence information showing the correspondence between the first measurement value and the second measurement value and a predetermined threshold (hereinafter also referred to as the first threshold), but also other correspondence information showing the correspondence between the third measurement value and other measurement values ​​(hereinafter also referred to as the fourth measurement value) and other predetermined thresholds (hereinafter also referred to as the third threshold).

[0109] Furthermore, the information processing device 1 may, for example, in step S12, make a determination as to whether the relationship between the first correspondence information and the second correspondence information, which shows the correspondence between the first measurement value and the second measurement value at the first timing, satisfies the first condition, and make a determination as to whether the relationship between the correspondence information (hereinafter also called the fifth correspondence information) and the sixth correspondence information, which shows the correspondence between the third measurement value and the fourth measurement value at the first timing, satisfies the condition (hereinafter also called the fourth condition). In addition, the information processing device 1 may, for example, in step S13, make a determination as to whether the attribute corresponding to the first timing satisfies the second condition if the relationship between the first correspondence information and the second correspondence information satisfies the first condition and the relationship between the fifth correspondence information and the sixth correspondence information satisfies the fourth condition.

[0110] Specifically, the information processing device 1 may, for example, in step S12, perform a determination of whether the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and a determination of whether the degree of deviation of the fifth corresponding information to the sixth corresponding information is greater than or equal to a third threshold. Furthermore, the information processing device 1 may, for example, in step S13, if the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and the degree of deviation of the fifth corresponding information to the sixth corresponding information is greater than or equal to a third threshold, perform a determination of whether the cause of the deviation of the first corresponding information to the second corresponding information being greater than or equal to a first threshold can be identified.

[0111] Furthermore, the information processing device 1 may, for example, in step S13, determine whether the attribute corresponding to the first timing satisfies the second condition if at least the relationship between the first corresponding information and the second corresponding information satisfies the first condition, or if at least the relationship between the fifth corresponding information and the sixth corresponding information satisfies the fourth condition.

[0112] Specifically, the information processing device 1 may, for example, in step S13, determine whether the cause of the deviation of the first corresponding information from the second corresponding information to the second corresponding information being equal to or greater than the first threshold is identifiable if at least the deviation of the fifth corresponding information from the sixth corresponding information to the third threshold is identifiable.

[0113] Furthermore, if the information processing device 1 determines, for example, that the relationship between the first corresponding information and the second corresponding information satisfies the first condition and the attribute corresponding to the first timing does not satisfy the second condition (YES in step S12 of Figure 5, NO in step S13 of Figure 5), it may further determine in step S14 whether the relationship between the fifth corresponding information and the sixth corresponding information satisfies the fourth condition, and if it determines that the relationship between the fifth corresponding information and the sixth corresponding information satisfies the fourth condition, it may output abnormal information.

[0114] Specifically, if the information processing device 1 determines, for example, that the degree of deviation of the first corresponding information to the second corresponding information is greater than or equal to a first threshold, and that the cause of the deviation of the first corresponding information to the second corresponding information being greater than or equal to the first threshold can be identified, then in step S14, it may further determine whether the degree of deviation of the fifth corresponding information to the sixth corresponding information is greater than or equal to a third threshold, and if the degree of deviation of the fifth corresponding information to the sixth corresponding information is greater than or equal to the third threshold, it may output abnormal information. [Explanation of symbols]

[0115] 1: Information processing device 2: Operating terminal 11: Sand pond 12: Landing well 13: Mixing pond 14: Forming pond 15: Sedimentation tank 16: Filtration tank 17: Water purification reservoir 18: Water distribution reservoir 10: Information processing systems 20: Processing equipment 101: CPU 102: Memory 103: Communication device 104: Storage medium 105: Output device 106: Bus 110: Program 130: Information storage area 1000: Processing system DT1: Measurement data DT1a: Measurement data G1: Graph G2: Graph G3: Graph G4: Graph P1: Pump P2: Pump P3: Pump P11: Pump T: Storage tank

Claims

1. A first measurement value for a first indicator related to the water to be treated at a first timing is obtained, and a second measurement value for a second indicator related to the water to be treated at the first timing is obtained. Referencing the second correspondence information which shows the correspondence between the first measurement and the second measurement at a second timing prior to the first timing, determine whether the relationship between the first correspondence information which shows the correspondence between the first measurement and the second measurement at the first timing and the second correspondence information satisfies the first condition. If it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition, then it is determined whether the attributes related to the measurement of the treated water at the first timing satisfy the second condition. An information output method that, if it is determined that the attribute corresponding to the first timing does not satisfy the second condition, outputs information indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition.

2. The information output method according to claim 1, wherein in the step of determining whether the first condition is met, the second correspondence information is referred to, and if it is determined that the degree of deviation of the first correspondence information with respect to the second correspondence information satisfies the other conditions, it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition.

3. Furthermore, other measured values ​​for other indicators related to the treated water at the first timing are obtained. The information output method according to claim 1, wherein in the step of determining whether the second condition is met, if the other measured values ​​meet the other conditions, it is determined that the attribute corresponding to the first timing meets the second condition.

4. The information output method according to claim 1, wherein in the step of determining whether the second condition is met, if the variation status of at least one of the first measurement value and the second measurement value within a predetermined time before and after the first timing satisfies the other conditions, it is determined that the attribute corresponding to the first timing satisfies the second condition.

5. Furthermore, if it is determined that the attribute corresponding to the first timing satisfies the second condition, the information output method according to claim 1 outputs information indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition and that the attribute corresponding to the first timing satisfies the second condition.

6. An information processing device for monitoring water to be treated in a treatment facility, A first measurement value for a first indicator related to the water to be treated at a first timing and a second measurement value for a second indicator related to the water to be treated at a first timing are obtained. Referencing the second correspondence information which shows the correspondence between the first measurement and the second measurement at a second timing prior to the first timing, determine whether the relationship between the first correspondence information which shows the correspondence between the first measurement and the second measurement at the first timing and the second correspondence information satisfies the first condition. If it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition, then it is determined whether the attributes related to the measurement of the treated water at the first timing satisfy the second condition. An information processing device that, when it is determined that the attribute corresponding to the first timing does not satisfy the second condition, outputs information indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition.

7. A processing system comprising a processing facility for processing water to be treated and an information processing device for monitoring the water to be treated, The aforementioned information processing device is A first measurement value for a first indicator related to the water to be treated at a first timing and a second measurement value for a second indicator related to the water to be treated at a first timing are obtained. Referencing the second correspondence information which shows the correspondence between the first measurement and the second measurement at a second timing prior to the first timing, determine whether the relationship between the first correspondence information which shows the correspondence between the first measurement and the second measurement at the first timing and the second correspondence information satisfies the first condition. If it is determined that the relationship between the first correspondence information and the second correspondence information satisfies the first condition, then it is determined whether the attributes related to the measurement of the treated water at the first timing satisfy the second condition. A processing system that, if it is determined that the attribute corresponding to the first timing does not satisfy the second condition, outputs information indicating that the relationship between the first corresponding information and the second corresponding information satisfies the first condition.

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