Information processing apparatus, program, and water treatment system

Abstract

To provide easy identification of factors that overlap with each other over time.SOLUTION: A water treatment system includes an acquisition part 110 acquiring time series data of water information at a plurality of water information acquisition points of the water treatment system, an extraction part 130 detecting peaks in each of the time series data acquired by the acquisition unit 110 and extracting at least one time-series data in which a peak occurs within a certain range from the timing of occurrence of the peak detected in the first time-series data, and an output part 140 outputting a device identification information associated with the at least one time-series data extracted by the extraction unit 130.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing device, a program, and a water treatment system. [Background technology]

[0002] Water treatment systems have been devised that stably supply treated water of the required quality or quantity from a water treatment system to a demand point (a supply destination of treated water from the water treatment system) (see, for example, Patent Document 1). The water treatment system described in Patent Document 1 mixes treated water obtained by treating each of a plurality of lines according to the required quality of the supply destination and supplies the water to the supply destination. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-110454 A Summary of the Invention [Problem to be solved by the invention]

[0004] In general, water treatment in a water treatment system involves a complex combination of treatment processes in multiple devices and water circulation. In a water treatment system, fluctuations in water quality occur due to this configuration. If multiple factors that deteriorate water quality overlap over time, the quality of the treated water may decline. In order to avoid a decline in the quality of the treated water, it is essential to identify the cause of the decline in water quality, but if multiple factors overlap over time, it is not easy to identify the cause of the decline in water quality. Therefore, some mechanism is needed to identify the cause.

[0005] An object of the present invention is to provide an information processing device, a program, and a water treatment system that can easily identify factors that overlap with each other in a chronological order. [Means for solving the problem]

[0006] The information processing device of the present invention comprises: An acquisition unit that acquires time-series data of water information at a plurality of water information acquisition points of the water treatment system; an extracting unit that detects a peak in each of the time series data acquired by the acquiring unit, and extracts at least one piece of time series data having a peak occurring within a certain range from the occurrence timing of the peak detected in a first time series data among the time series data; The apparatus further includes an output unit that outputs device identification information associated with at least one piece of time-series data extracted by the extraction unit.

[0007] In addition, the program of the present invention is On the computer, A step of acquiring time series data of water information at a plurality of water information acquisition points of the water treatment system; detecting a peak in each of the acquired time series data, and extracting at least one piece of time series data having a peak occurring within a certain range from the occurrence timing of the peak detected in a first time series data among the time series data; and outputting device identification information associated with the at least one extracted time-series data.

[0008] In addition, the water treatment system of the present invention includes A water treatment device and an information treatment device are provided. The information processing device includes: An acquisition unit that acquires time series data of water information at a plurality of water information acquisition points that are the plurality of water treatment devices or paths between the plurality of water treatment devices; an extracting unit that detects a peak in each of the time series data acquired by the acquiring unit, and extracts at least one piece of time series data having a peak occurring within a certain range from the occurrence timing of the peak detected in a first time series data among the time series data; The apparatus further includes an output unit that outputs device identification information associated with at least one piece of time-series data extracted by the extraction unit. Effect of the Invention

[0009] In the present invention, factors that overlap with each other in a chronological order can be easily identified. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing a water treatment system according to a first embodiment. [Diagram 2] 2 is a diagram illustrating an example of components included in the information processing device illustrated in FIG. 1. [Diagram 3] 2 is a diagram showing an example of a graph in which time series data of measurement data measured by the water quality measuring instrument shown in FIG. 1 and time series data of measurement data measured by a flow meter are overlapped in time series. FIG. [Figure 4] 3 is a diagram showing, on a graph, an example of identification information assigned to each of the divided data obtained by dividing the time-series data by the dividing unit shown in FIG. 2. FIG. [Diagram 5] 2 is a flowchart illustrating an example of an information processing method in the information processing device shown in FIG. [Figure 6] FIG. 13 is a diagram showing a water treatment system according to a second embodiment. [Figure 7] 7 is a diagram illustrating an example of components included in the information processing device illustrated in FIG. 6. [Figure 8] 8 is a diagram showing an example of association between time-series data and device identification information stored in a storage unit shown in FIG. 7. FIG. [Figure 9] 7 is a flowchart illustrating an example of an information processing method in the information processing device shown in FIG. 6. [Figure 10] FIG. 13 is a diagram showing a water treatment system according to a third embodiment. [Figure 11] 11 is a diagram illustrating an example of components included in the information processing device illustrated in FIG. 10. [Figure 12] 11 is a diagram showing an example of how the measurement data of the water quality measuring instrument changes when the operation of the water treatment device shown in FIG. 10 is changed. FIG. [Figure 13] 11 is a flowchart illustrating an example of an information processing method in the information processing device shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. (First embodiment)

[0012] Fig. 1 is a diagram showing a water treatment system according to a first embodiment. As shown in Fig. 1, a water treatment system 10 according to this embodiment includes a water treatment facility (ultrapure water production facility) 21 and an information processing device 100.

[0013] The water treatment facility 21 includes a pretreatment facility 22, a primary pure water production facility 23, and a secondary pure water production facility (subsystem) 24. In this embodiment, an example will be described in which the present invention is applied to the primary pure water production facility 23. The pretreatment facility 22 may be a facility used in general water treatment facilities, and is a device that removes fine particles from the raw water that is supplied. The secondary pure water production facility 24 may be a facility used in general water treatment facilities, and is a facility that removes trace amounts of ions and total organic carbon that could not be completely removed by the primary pure water production facility 23. It is also possible to apply the present invention to the pretreatment facility 22 and the secondary pure water production facility 24.

[0014] The primary pure water manufacturing equipment 23 has a tank 200, water treatment devices 300 and 400, a water quality measuring device 210 which is a water quality acquisition unit, and flow meters 310 and 410 which are flow rate acquisition units. The information processing device 100, the water quality measuring device 210, and the flow meters 310 and 410 may be directly connected to each other so as to be able to communicate with each other, or may be connected via a communication network. The information processing device 100, the water quality measuring device 210, and the flow meters 310 and 410 may be connected wirelessly or via wires.

[0015] The tank 200 is a tank for storing treated water (pretreated water) supplied from the pretreatment facility 22. The pretreated water stored in the tank 200 is supplied to the downstream water treatment device 300 as water to be treated.

[0016] In this embodiment, the water treatment device 300 is an RO (reverse osmosis membrane separation device). The water treatment device 300 is supplied with water to be treated stored in a tank 200, and performs a predetermined treatment on the supplied water to be treated. The water treatment device 300 separates, for example, ions and TOC (Total Organic Carbon), and separates the water into permeated water and concentrated water. The water treatment device 300 may be a device other than an RO, or may be composed of an RO and another device.

[0017] In this embodiment, the water treatment device 400 is an EDI (electrically regenerated pure water device). The water treatment device 400 is supplied with treated water treated in the water treatment device 300 and performs a predetermined process on the treated water. The water treatment device 400 may be, for example, an EDI (electrically regenerated pure water device). The water treatment device 400 performs, for example, desalination and separates the water into desalted water and concentrated water. The water treatment device 400 may be a device other than an EDI, or may be composed of an EDI and another device. A part of the treated water treated in the water treatment device 400 is returned to the tank 200 as circulating water. That is, the tank 200 also stores circulating water, which is a part of the treated water treated in the water treatment device 400. If the water treatment device 400 is an EDI, the treated water returned to the tank 200 may be desalted water (permeated water) treated in the EDI, concentrated water, or electrode water.

[0018] The water quality measuring instrument 210 measures (acquires) the water quality of the water to be treated stored in the tank 200 as water information. The measurement points at which the water quality measuring instrument 210 measures the water quality are water information acquisition points. The water quality measured by the water quality measuring instrument 210 is, for example, TOC. The water quality measuring instrument 210 transmits the measured values ​​to the information processing device 100 as time-series data.

[0019] The flow meter 310 measures the flow rate of treated water supplied from the water treatment device 300 as water information. The measurement points at which the flow meter 310 measures the flow rate are water information acquisition points. The flow meter 310 transmits the measured value to the information processing device 100 as time-series data.

[0020] The flow meter 410 measures, as water information, the flow rate of treated water circulated to the tank 200 as circulating water among treated water supplied from the water treatment device 400. The measurement point at which the flow meter 410 measures the flow rate is the water information acquisition point. The flow meter 410 transmits the measured value to the information processing device 100 as time-series data.

[0021] Fig. 2 is a diagram showing an example of components included in the information processing device 100 shown in Fig. 1. As shown in Fig. 2, the information processing device 100 shown in Fig. 1 has an acquisition unit 110, a division unit 120, an extraction unit 130, and an output unit 140. Note that Fig. 2 shows main elements in this embodiment among the components included in the information processing device 100 shown in Fig. 1.

[0022] The acquisition unit 110 acquires time series data of water information at each of a plurality of water information acquisition points of the water treatment system 10. In the water treatment system 10 shown in FIG. 1, the acquisition unit 110 acquires time series data of water information at each of the above-mentioned three water information acquisition points. More specifically, the acquisition unit 110 acquires time series data of water quality transmitted from the water quality measuring device 210, time series data of flow rate transmitted from the flow meter 310, and time series data of flow rate transmitted from the flow meter 410. The acquisition unit 110 outputs the acquired time series data to the division unit 120. The water information acquired by the acquisition unit 110 may be information indicating water quality, information indicating the control contents (e.g., opening and closing of valves) and operation processes of devices provided in the water treatment system 10, information indicating the water level of the tank 200, information indicating the flow rate, information indicating the water pressure, or the like, or at least one of these. By using such information that is thought to affect the water quality in the water treatment system, it is possible to easily identify the cause of the water quality fluctuation. The acquisition unit 110 may acquire multiple types of water information from each water information acquisition point. For example, the acquisition unit 110 may acquire three pieces of water information, namely, flow rate, water pressure, and water quality, from one water information acquisition point. The acquisition unit 110 may also acquire an image of water at the water information acquisition point as the water information. The image acquired by the acquisition unit 110 may be subjected to a predetermined image processing to acquire data for determining the amount of bubbles generated in the water, information such as the size and shape of flocs may be acquired from an image of flocs in treated water to which a coagulant has been added, data for determining the color and degree of turbidity of water may be acquired from an image of wastewater, and data for determining the presence, amount, and area of ​​an oil film may be acquired from an image of water stored in a tank.

[0023] The dividing unit 120 divides each piece of time series data output from the acquiring unit 110 into a plurality of divided data on the time axis for each water information acquisition point. At this time, the dividing unit 120 divides each piece of time series data into regions on the time axis that correspond to each other among a plurality of water information acquisition points (for example, time periods, cycle numbers of resins used as water treatment devices (numbers indicating how many times water has been regenerated before passing water through them), operating processes, etc.). The width (interval) of these regions on the time axis is set based on the flow rate, length of the path, treatment time in each device, operating process time, etc. The dividing unit 120 assigns identification information to each piece of divided data. The dividing unit 120 assigns identification information to each piece of divided data that indicates at which water information acquisition point the divided data was acquired and which region it belongs to. For example, when the acquisition unit 110 acquires water information from three water information acquisition points "A" to "C" and the corresponding regions are ten regions "001" to "010", the identification information of the divided data obtained by dividing the time series data acquired from the water information acquisition point "A" is "A001" to "A010", the identification information of the divided data obtained by dividing the time series data acquired from the water information acquisition point "B" is "B001" to "B010", and the identification information of the divided data obtained by dividing the time series data acquired from the water information acquisition point "C" is "C001" to "C010". In this case, for example, the divided data "A001", the divided data "B001", and the divided data "C001" are divided data corresponding to each other. Note that the number of mutually corresponding regions may not be one, but may be multiple regions before and after each other. For example, the divided data corresponding to the divided data "A002" may be "B001" to "B003" and "C001" to "C003". The positions of the corresponding divided data on the time axis do not need to be exactly the same as each other, and may be shifted by a time amount that takes into account delays in water treatment. Specifically, for example, the position of the divided data "B001" on the time axis may be the same as the position of the divided data "A001" on the time axis, or may be delayed from the position of the divided data "A001" on the time axis by an amount that takes into account the time it takes for water to arrive from the water information acquisition point "A" to the water information acquisition point "B".

[0024] The extraction unit 130 detects the peaks of each of the time series data output from the acquisition unit 110. The peaks may be the peaks showing the maximum value or the minimum value when the measured values ​​are plotted on a graph in a time series. The peaks may also be the longest period during which the measured values ​​exceed a predetermined range. The peaks are not limited to the measured values ​​of water quality or flow rate, and may be, for example, the change points of the open / closed state of a valve or the change points of an operation process. The same applies to the peaks in the following description. The detection of the peaks may be performed using a Python library such as scipy, and the detection means is not specified. Then, the extraction unit 130 extracts at least one piece of time series data in which a peak occurs within a certain range from the occurrence timing of the peak detected in the first time series data at the first water information acquisition point to be improved among the time series data. Specifically, the extraction unit 130 extracts the divided data including the detected peak. Then, when a peak of water information is included in the divided data of the second time series data at the second water information acquisition point corresponding to the divided data extracted from the first time series data, the extraction unit 130 extracts the second time series data. Here, the second water information acquisition point is a reference point that supplies water to the first water information acquisition point (a water information acquisition point other than the water information acquisition point at which the time series data to be improved is acquired). For example, the above-mentioned water information acquisition point "A" is the first water information acquisition point, and the water information acquisition point "B" and the water information acquisition point "C" are the second water information acquisition points. When a peak of water information is included in the divided data "A001" and the divided data "A006" obtained by dividing the time series data acquired from the water information acquisition point "A", and when a peak of water information is included in the divided data "B001" of the divided data "B001" and the divided data "C001" corresponding to the divided data "A001", the extraction unit 130 extracts the time series data of the water information acquisition point "B". At this time, the extraction unit 130 may extract the divided data "B001".

[0025] The output unit 140 outputs the second time series data extracted by the extraction unit 130. When the extraction unit 130 extracts divided data, the output unit 140 may output the divided data extracted by the extraction unit 130. By outputting the divided data, it is possible to identify the timing of the occurrence of the cause. Furthermore, the output unit 140 may output time series data having the largest number of divided data including peaks of water information, which corresponds to the divided data including peaks of water information in the first time series data, among the second time series data extracted by the extraction unit 130. Specifically, for example, when the divided data "A001" and the divided data "A006" obtained by dividing the time-series data acquired from the water information acquisition point "A" contain a peak of water information, the divided data "B001" of the divided data "B001" and the divided data "C001" corresponding to the divided data "A001" contains a peak of water information, and the divided data "B006" and the divided data "C006" corresponding to the divided data "A006" both contain a peak of water information, the output unit 140 outputs the time-series data of the water information acquisition point "B". The time-series data with the largest number of divided data containing the peak of water information of the water information acquisition point, which is the reference point, is considered to have the highest probability of affecting the water information acquisition point to be improved. Therefore, by outputting the time-series data with the largest number of divided data containing the peak of water information of the water information acquisition point, which is the reference point, the cause can be identified more accurately. Furthermore, the output unit 140 may multiply the number of divided data pieces including a peak of the water information at the water information acquisition point, which is the reference point, by a preset weighting coefficient, and output the time series data with the maximum value. This weighting coefficient may be determined based on the degree of influence on the water quality of the treated water supplied to the subsequent stage according to the change in the time series data. For example, when the water information is flow rate data, the output unit 140 may output the time series data with the maximum value obtained by multiplying the number of divided data pieces including a peak by a weighting coefficient of 1.5, and when the water information indicates an operating process, the output unit 140 may output the time series data with the maximum value obtained by multiplying the number of divided data pieces including a peak by a weighting coefficient of 2.The output unit 140 may also calculate a correlation coefficient between the time series data of the comparison source and the time series data of the comparison target, and determine the time series data to be output based on the calculated value. Time series data with many peaks is easily detected due to logic reasons. Therefore, filtering can be performed by calculating the correlation coefficient between the time series data. The output unit 140 may display the second time series data or the divided data on a display or the like, may print it, or may transmit it to another device.

[0026] Fig. 3 is a diagram showing an example of a graph in which time series data of measurement data measured by the water quality measuring instrument 210 shown in Fig. 1 and time series data of measurement data measured by the flow meters 310, 410 are overlapped in time series. Fig. 4 is a diagram showing, on a graph, an example of identification information given to each of the divided data into which the time series data is divided by the dividing unit 120 shown in Fig. 2. In Figs. 3 and 4, the horizontal axis indicates time, and the vertical axis indicates water quality (the higher the position, the higher the water quality) or flow rate.

[0027] In the graph shown in FIG. 3, the time series data of the measurement data measured by the water quality measuring instrument 210, the time series data of the measurement data measured by the flowmeter 310, and the time series data of the measurement data measured by the flowmeter 410 are displayed overlapping on the same time axis. In addition, in the graph shown in FIG. 3, the peaks of the water information in each of the time series data are indicated by surrounding them with dashed lines. Furthermore, the division unit 120 divides each of these time series data into a plurality of divided data ("001" to "009" in the example shown in FIG. 3). Furthermore, the division unit 120 assigns identification information to each of the divided data. As shown in FIG. 4, the division unit 120 assigns identification information "A001" to "A009" to each of the divided data divided from the time series data of the measurement data measured by the water quality measuring instrument 210. Furthermore, the division unit 120 assigns identification information "B001" to "B009" to each of the divided data divided from the time series data of the measurement data measured by the flowmeter 310. Furthermore, the dividing unit 120 assigns identification information "C001" to "C009" to each of the divided data divided from the time-series data of the measurement data measured by the flowmeter 410.

[0028] As shown in FIG. 4, the extraction unit 130 extracts the divided data "A004" and "A007" including a peak from the divided data obtained by dividing the time series data of the measurement data measured by the water quality measuring instrument 210. Next, the extraction unit 130 determines whether the divided data "B004" corresponding to the divided data "A004" includes the peak of the measurement data measured by the flowmeter 310 from the divided data obtained by dividing the time series data of the measurement data measured by the flowmeter 310. The extraction unit 130 also determines whether the divided data "B007" corresponding to the divided data "A007" includes the peak of the measurement data measured by the flowmeter 310 from the divided data obtained by dividing the time series data of the measurement data measured by the flowmeter 310. If the divided data "B004" or the divided data "B007" includes the peak of the measurement data measured by the flowmeter 310, the extraction unit 130 extracts the time series data of the measurement data measured by the flowmeter 310. At this time, the extraction unit 130 may extract the divided data "B004" and the divided data "B007". Furthermore, the extraction unit 130 determines whether or not the divided data "C004" corresponding to the divided data "A004" includes a peak of the measurement data measured by the flowmeter 410 from the divided data obtained by dividing the time series data of the measurement data measured by the flowmeter 410. Furthermore, the extraction unit 130 determines whether or not the divided data "C007" corresponding to the divided data "A007" includes a peak of the measurement data measured by the flowmeter 410 from the divided data obtained by dividing the time series data of the measurement data measured by the flowmeter 410. If the divided data "C004" or the divided data "C007" includes a peak of the measurement data measured by the flowmeter 410, the extraction unit 130 extracts the time series data of the measurement data measured by the flowmeter 410. At this time, the extraction unit 130 may extract the divided data "C004" and the divided data "C007".

[0029] The following describes an information processing method in the information processing device 100 shown in Fig. 1. Fig. 5 is a flowchart for explaining an example of the information processing method in the information processing device 100 shown in Fig. 1.

[0030] First, the acquisition unit 110 acquires time-series data of water information at each of a plurality of water information acquisition points provided in the water treatment system (step S1). Then, the division unit 120 divides each of the time-series data acquired by the acquisition unit 110 into a plurality of divided data on the time axis for each water information acquisition point (step S2). The division unit 120 assigns identification information to each of the divided divided data (step S3).

[0031] Next, the extraction unit 130 detects a peak of water information from the time series data to be improved, and extracts divided data including the detected peak (step S4). The extraction unit 130 determines whether or not the divided data of the time series data at the reference point corresponding to the extracted divided data includes a peak of water information (step S5). If the corresponding divided data includes a peak of water information, the extraction unit 130 extracts the time series data (step S6). The output unit 140 outputs the time series data extracted by the extraction unit 130 in step S6 (step S7).

[0032] In general, in a water treatment system consisting of multiple water treatment devices, it is not easy to design and operate the system so that multiple factors that cause fluctuations in the quality of the treated water do not overlap with each other. The reason is that in reality, the water treatment system must be operated according to fluctuations in the required water quality and water volume at the demand point, and it is difficult to predict such fluctuations and design the system so that multiple factors that cause fluctuations in the quality of the treated water do not overlap with each other. Another reason is that it is difficult to estimate the factors that cause fluctuations in the quality of the treated water. Another reason is that when multiple factors are considered to be the cause of water quality fluctuations, it is difficult to identify the factors.

[0033] Therefore, in this embodiment, time series data of water information is acquired at each of a plurality of water information acquisition points provided in the water treatment device and the path constituting the water treatment system, and each acquired time series data is divided into a plurality of divided data on the time axis for each water information acquisition point. Identification information is assigned to each divided divided data. A peak of water information is detected from the time series data to be improved, and divided data including the detected peak is extracted. If the divided data of the time series data at the water information acquisition point that is the reference point corresponding to the extracted divided data includes a peak of water information, the time series data is extracted, and the extracted time series data is output. For example, if the device in the preceding stage is a tank, a drop in the water level of the tank is considered to cause a drop in the water quality of the device in the following stage. Also, a decrease in the flow rate of water supplied to the circulation path is considered to cause a drop in the water quality of the device in the following stage. In this way, the areas including the peaks in the time series data are compared with each other, and the extracted time series data is output as a result of the comparison. This makes it possible to easily identify factors that overlap with each other in the time series. The output result is used to analyze the factors of the water quality fluctuation. The analysis may be performed using a computer program installed in a specified calculation device. When the water quality fluctuation exceeds a predetermined standard, if the cause of the fluctuation can be identified, the fluctuation in water quality can be suppressed (improved) by eliminating the cause. For example, in a system in which activated carbon → resin → RO → EDI are arranged in this order, if there is a TOC peak at the outlet of the EDI and the timing of resin regeneration and the timing of opening and closing the RO circulation valve coincide with the peak, it can be assumed that at least one of them is considered to be the cause of the water quality fluctuation, and that the peak can be suppressed by shifting the timing so that they do not coincide with each other. In addition, the time-series data handled by the information processing device 100 may be water information as it is, or may be data obtained by performing preprocessing such as resampling to change the frequency of data, noise cutting, time averaging, scaling such as standardization and normalization, trend removal, periodicity removal, outlier processing, and Fourier transform. (Second embodiment)

[0034] FIG. 6 is a diagram showing a water treatment system according to a second embodiment. As shown in FIG. 6, a water treatment system 11 according to this embodiment includes a water treatment facility (ultrapure water production facility) 21 and an information processing device 101. The water treatment facility (ultrapure water production facility) 21 may be the same as that in the first embodiment. The information processing device 101, the water quality measuring device 210, and the flow meters 310, 410 may be directly connected to each other so as to be able to communicate with each other, or may be connected via a communication network. The information processing device 101, the water quality measuring device 210, and the flow meters 310, 410 may be connected wirelessly or via a wire.

[0035] Fig. 7 is a diagram showing an example of components included in the information processing device 101 shown in Fig. 6. As shown in Fig. 7, the information processing device 101 shown in Fig. 6 has an acquisition unit 110, a division unit 120, an extraction unit 130, an output unit 141, a storage unit 151, and a readout unit 161. The acquisition unit 110, the division unit 120, and the extraction unit 130 may be the same as those in the first embodiment. Note that Fig. 7 shows main elements in this embodiment among the components included in the information processing device 101 shown in Fig. 6.

[0036] The storage unit 151 stores the time series data at each of the multiple water information acquisition points in association with the device identification information indicating the device capable of controlling the timing at which the peak of the time series data occurs. FIG. 8 is a diagram showing an example of the association between the time series data and the device identification information stored in the storage unit 151 shown in FIG. 7. As shown in FIG. 8, the storage unit 151 shown in FIG. 7 stores information indicating the time series data and the device identification information in association with each other. The information indicating the time series data may be information specific to each of the time series data acquired by the acquisition unit 110, and may be, for example, information that can identify each of the water information acquisition points or information that can identify the device or equipment (for example, the water quality measuring device 210, the flowmeters 310, 410, etc. shown in FIG. 6) that acquires the water information at the water information acquisition point. The device identification information is information that can identify the device that can control the timing at which the peak of the time series data occurs. For example, in the embodiment shown in FIG. 6, the device that can control the timing at which the peak of the time series data acquired by the flowmeter 310 occurs is the water treatment device 300 arranged in front of the flowmeter 310. Therefore, information indicating the time series data acquired by the flowmeter 310 is associated with information that can identify the water treatment device 300. In addition, the device that can control the timing at which the peak of the time series data acquired by the flowmeter 410 occurs is the water treatment device 400 arranged in the front stage of the flowmeter 410. In this case, information indicating the time series data acquired by the flowmeter 410 is associated with information that can identify the water treatment device 400. In FIG. 8, information indicating the time series data "Axxx", "Bxxx" and "Cxxx" are associated with the device identification information "M1". This indicates that the device to which the device identification information "M1" is assigned can control the timing at which the peak of the time series data indicated by "Axxx", the time series data indicated by "Bxxx" and the time series data indicated by "Cxxx" occurs. In addition, information indicating the time series data "Dxxx" is associated with the device identification information "M2". This indicates that the timing at which the peak of the time-series data indicated by "DXXX" occurs can be controlled by the device to which device identification information "M2" is assigned. In addition, the information indicating the time-series data, "EXXX" and "FXXX", are associated with device identification information "M3".This indicates that the timing at which peaks occur in the time series data indicated by "Exxx" and the time series data indicated by "Fxxx" is controllable by the device to which device identification information "M3" is assigned.

[0037] The reading unit 161 reads out the device identification information stored in the storage unit 151 in association with the second time series data extracted by the extraction unit 130 from the storage unit 151. Specifically, the reading unit 161 reads out the device identification information associated with the information indicating the second time series data extracted by the extraction unit 130 from the storage unit 151, using the information indicating the second time series data extracted by the extraction unit 130 as a search key. The reading unit 161 outputs the device identification information read out from the storage unit 151 to the output unit 141.

[0038] The output unit 141 outputs the device identification information output from the readout unit 161. At this time, the output unit 141 may output only the device identification information with the largest number of device identification information output from the readout unit 161. For example, when the correspondence shown in FIG. 8 is stored in the storage unit 151 and the information indicating the time series data extracted by the extraction unit 130 is "Axxx", "Bxxx", "Dxxx" and "Exxx", the device identification information read by the readout unit 161 is "M1", "M1", "M2" and "M3", so that the output unit 141 may output only the device identification information "M1" with the largest number among them. Also, as in the first embodiment, a weighting coefficient may be used. This makes it possible to recognize a device that is more likely to be the cause of the peak of the first time series data. Also, the output unit 141 may display the device identification information with emphasis as the number of device identification information output from the readout unit 161 increases. The manner of outputting the device identification information may be the same as in the first embodiment.

[0039] The following describes an information processing method in the information processing device 101 shown in Fig. 6. Fig. 9 is a flowchart for explaining an example of the information processing method in the information processing device 101 shown in Fig. 6.

[0040] First, the acquisition unit 110 acquires time-series data of water information at each of a plurality of water information acquisition points provided in the water treatment system (step S11). Then, the division unit 120 divides each of the time-series data acquired by the acquisition unit 110 into a plurality of divided data on the time axis for each water information acquisition point (step S12). The division unit 120 assigns identification information to each of the divided divided data (step S13).

[0041] Next, the extraction unit 130 detects a peak of water information from the time series data to be improved, and extracts divided data including the detected peak (step S14). The extraction unit 130 determines whether or not the divided data of the time series data at the reference point corresponding to the extracted divided data includes a peak of water information (step S15). If the corresponding divided data includes a peak of water information, the extraction unit 130 extracts the time series data (step S16).

[0042] Next, the reading unit 161 reads the device identification information from the storage unit 151 based on the time-series data extracted by the extraction unit 130 (step S17). The specific reading method is as described above. Then, the output unit 141 outputs the device identification information read by the reading unit 161 (step S18).

[0043] In this manner, in addition to the first embodiment, in this embodiment, when a peak is included in the divided data of the second time series data at a reference point corresponding to the divided data including the peak of the first time series data to be improved, device identification information of a device capable of controlling the timing of occurrence of the peak of the time series data is output. This makes it possible to identify a device assumed to be the cause of the peak of the first time series data. (Third embodiment)

[0044] Fig. 10 is a diagram showing a water treatment system according to a third embodiment. As shown in Fig. 10, a water treatment system 12 according to this embodiment includes a water treatment facility (ultrapure water production facility) 21 and an information processing device 102. The water treatment facility (ultrapure water production facility) 21 may be the same as that in the first embodiment. The information processing device 102, the water quality measuring device 210, and the flow meters 310, 410 may be directly connected to each other so as to be able to communicate with each other, or may be connected via a communication network. The information processing device 102, the water quality measuring device 210, and the flow meters 310, 410 may be connected wirelessly or via a wire.

[0045] FIG. 11 is a diagram showing an example of components included in the information processing device 102 shown in FIG. 10. As shown in FIG. 1, the information processing device 102 shown in FIG. 10 has an acquisition unit 110, a division unit 120, an extraction unit 130, a storage unit 151, a readout unit 161, and an operation control unit 172. The acquisition unit 110, the division unit 120, and the extraction unit 130 may be the same as those in the first embodiment. The storage unit 151 and the readout unit 161 may be the same as those in the second embodiment. Note that FIG. 11 shows main elements in this embodiment among the components included in the information processing device 102 shown in FIG. 10. In addition, the information processing device 102 may be equipped with the output unit 141 described in the second embodiment.

[0046] The operation control unit 172 controls the operation of the device indicated by the device identification information read by the read unit 161 so that the timing of the time series data extracted by the extraction unit 130 is changed. The operation control unit 172 controls the operation of the device indicated by the device identification information read by the read unit 161 so that the divided data having a peak in the first time series data and the divided data having a peak in the time series data extracted by the extraction unit 130 do not overlap each other on the time axis, that is, so that they do not have a relative relationship of corresponding divided data (so that the timing does not affect each other). For example, the operation control unit 172 changes the timing of the operation process of the device indicated by the device identification information read by the read unit 161. Alternatively, the operation control unit 172 changes the order or number of times of each operation process of the device indicated by the device identification information read by the read unit 161. Alternatively, the operation control unit 172 changes the opening and closing timing of the opening and closing valve in the device indicated by the device identification information read by the read unit 161. Alternatively, the operation control unit 172 changes the number of times an on-off valve is opened and closed in the device indicated by the device identification information read by the reading unit 161. The operation control unit 172 may control the operation of the device that is capable of controlling the timing of the first time-series data to be improved. The operation control unit 172 may also control the device indicated by the device identification information read by the reading unit 161, and apply an interlock to prevent processes from overlapping with other devices.

[0047] Fig. 12 is a diagram showing an example of changes in the measurement data of the water quality measuring instrument 210 when the operation of the water treatment device 300 shown in Fig. 10 is changed. As shown in Fig. 12, the operation control unit 172 controls (changes) the operation of the water treatment device 300, thereby changing the timing of the time series data measured by the flowmeter 310. As a result, the timing of the peak on the time axis in the divided data including the peak of the time series data measured by the flowmeter 310 and the timing of the peak on the time axis in the divided data including the peak of the time series data measured by the flowmeter 410 do not overlap (they become separated from each other on the time axis). As a result, the peak of the water information (water quality value) that appeared in the time series data of the water quality measuring instrument 210 that measures the water quality of the tank 200 arranged in the rear stage of the water treatment devices 300, 400 becomes lower, and the fluctuation range of the water quality can be reduced.

[0048] The following describes an information processing method in the information processing device 102 shown in Fig. 10. Fig. 13 is a flowchart for explaining an example of an information processing method in the information processing device 102 shown in Fig. 10.

[0049] First, the acquisition unit 110 acquires time-series data of water information at each of a plurality of water information acquisition points provided in the water treatment system (step S21). Then, the division unit 120 divides each of the time-series data acquired by the acquisition unit 110 into a plurality of divided data on the time axis for each water information acquisition point (step S22). The division unit 120 assigns identification information to each of the divided divided data (step S23).

[0050] Next, the extraction unit 130 detects a peak of water information from the time series data to be improved, and extracts divided data including the detected peak (step S24). The extraction unit 130 determines whether or not the divided data of the time series data at the reference point corresponding to the extracted divided data includes a peak of water information (step S25). If the corresponding divided data includes a peak of water information, the extraction unit 130 extracts the time series data (step S26).

[0051] Next, the readout unit 161 reads out the device identification information from the storage unit 151 based on the time series data extracted by the extraction unit 130 (step S27). The specific readout method is as described above. Then, the operation control unit 172 causes the device indicated by the device identification information read out by the readout unit 161 to change the timing of the time series data extracted by the extraction unit 130 and perform operation (step S28).

[0052] Thus, in this embodiment, in addition to the first embodiment, when the divided data of the second time series data at the reference point corresponding to the divided data containing the peak of the first time series data to be improved contains a peak, the operation of a device capable of controlling the timing of the time series data is controlled (changed).By controlling (changing) the operation of a device assumed to be the cause of the peak of the first time series data, the peak of the first time series data can be reduced, and the fluctuation range of the water quality can be reduced.

[0053] Although the above description has been given with each component assigned to each function (process), this assignment is not limited to the above. In addition, the configuration of the components is also not limited to the above-mentioned form, and the above-mentioned form is merely an example. In addition, the above-mentioned embodiments may be combined in any combination.

[0054] The processes performed by each of the information processing devices 100 to 102 may be performed by a logic circuit that is created for each purpose. Alternatively, a computer program (hereinafter referred to as a program) in which the process contents are described as a procedure may be recorded on a recording medium that can be read by each of the information processing devices 100 to 102, and the program recorded on the recording medium may be read and executed by each of the information processing devices 100 to 102. The recording medium that can be read by each of the information processing devices 100 to 102 refers to a removable recording medium such as a floppy (registered trademark) disk, a magneto-optical disk, a DVD (Digital Versatile Disc), a CD (Compact Disc), a Blu-ray (registered trademark) Disc, a USB (Universal Serial Bus) memory, and an SD card, as well as memories such as a ROM (Read Only Memory), a RAM (Random Access Memory), and a HDD (Hard Disc Drive) that are built into each of the information processing devices 100 to 102. The program recorded on the recording medium is read by a CPU (not shown) provided in each of the information processing devices 100 to 102, and the same processing as described above is performed under the control of the CPU. Here, the CPU operates as a computer that executes the program read from the recording medium on which the program is recorded. [Explanation of symbols]

[0055] 10~12 Water treatment system 21 Water treatment facilities 22 Pretreatment Equipment 23 Primary pure water production equipment 24 Secondary pure water production equipment 100~102 Information processing equipment 110 Acquisition Department 120 Division 130 Extraction part 140,141 Output section 151 Storage section 161 Readout section 172 Operation control unit 200 Tank 210 Water quality meter 300,400 Water treatment equipment 310,410 Flowmeter

Claims

1. An acquisition unit that acquires time-series data of water information at a plurality of water information acquisition points of the water treatment system; an extracting unit that detects a peak in each of the time series data acquired by the acquiring unit, and extracts at least one piece of time series data having a peak occurring within a certain range from the occurrence timing of the peak detected in a first time series data among the time series data; an output unit that outputs device identification information associated with at least one piece of time-series data extracted by the extraction unit.

2. 2. The information processing device according to claim 1, A division unit that divides each of the time series data acquired by the acquisition unit into a plurality of divided data on a time axis, the extraction unit extracts the divided data including a peak of the water information from first time series data at a first water information acquisition point among the plurality of water information acquisition points, and extracts the second time series data when the peak of the water information is included in divided data of second time series data at a second water information acquisition point that supplies water to the first water information acquisition point and corresponds to the extracted divided data; The output unit outputs device identification information associated with the second time-series data extracted by the extraction unit.

3. 3. The information processing device according to claim 2, the extraction unit extracts, from the second time series data, divided data that corresponds to the divided data extracted from the first time series data and includes the peak; The output unit is an information processing device that outputs the divided data extracted by the extraction unit.

4. 3. The information processing device according to claim 1, a storage unit that stores the time-series data at each of the plurality of water information acquisition points in association with the device identification information indicating a device that can control the timing at which a peak occurs in the time-series data; a read unit that reads, from the storage unit, device identification information that is stored in the storage unit in association with the time-series data extracted by the extraction unit, The output unit outputs the device identification information read by the reading unit.

5. 5. The information processing device according to claim 4, An information processing device having an operation control unit that changes the timing of the time series data to cause an apparatus indicated by the apparatus identification information read by the reading unit to operate.

6. 4. The information processing device according to claim 2, The output unit performs a predetermined calculation on the number of divided data items including the peak of water information that correspond to the divided data items including the peak of water information in the first time series data, among the second time series data extracted by the extraction unit, and outputs the time series data for which the value of the result of the calculation is maximum.

7. 3. The information processing device according to claim 1, An information processing device in which the water information is at least one of information indicating water quality, information indicating the control contents of devices provided in the water treatment system, information indicating the water level in a tank, information indicating the flow rate, and information indicating water pressure.

8. On the computer, A step of acquiring time series data of water information at a plurality of water information acquisition points of the water treatment system; detecting a peak in each of the acquired time series data, and extracting at least one piece of time series data having a peak within a certain range from the occurrence timing of the peak detected in a first time series data from among the time series data; and outputting device identification information associated with the at least one extracted time-series data.

9. A water treatment device and an information treatment device are provided. The information processing device includes: An acquisition unit that acquires time series data of water information at a plurality of water information acquisition points that are the plurality of water treatment devices or paths between the plurality of water treatment devices; an extracting unit that detects a peak in each of the time series data acquired by the acquiring unit, and extracts at least one piece of time series data having a peak occurring within a certain range from the occurrence timing of the peak detected in a first time series data among the time series data; an output unit that outputs apparatus identification information associated with at least one of the time-series data extracted by the extraction unit.

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