Control apparatus, control method thereof, and control program

Abstract

To provide maintenance of both the flow rate of coagulated sludge supplied to a dehydrator and a water content of a dehydrated cake discharged from the dehydrator in a prescribed range.SOLUTION: A control unit (10) includes an acquisition unit (101) for acquiring measurement data including at least a flow rate of coagulated sludge supplied to a screw press type dehydrator that dehydrates the coagulated sludge during transportation, a prediction unit (102) for predicting a water content of the dehydrated cake to be discharged from the dehydrator at a point in time when a residence time has elapsed from the measured on-time point of the measurement data by using the measurement data, and an indication unit (103) for indicating a rotational speed of a screw so that the flow rate of the coagulated sludge falls within a first predetermined range if the flow rate of the coagulated sludge is outside the first predetermined range while indicating the rotational speed of the screw so that the water content of the dehydrated cake falls within a second predetermined range if the flow rate of the coagulated sludge is within the first predetermined range and a predicted value of the water content of the dehydrated cake is outside the second predetermined range.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a technique for controlling sludge treatment. [Background technology]

[0002] Sludge treatment carried out in wastewater treatment facilities such as sewage treatment plants includes a process of dehydrating sludge with a dehydrator. For efficient sludge treatment, it is important to maintain the flow rate of sludge supplied to the dehydrator within a predetermined range and to maintain the moisture content of the dehydrated cake obtained by dehydration within a predetermined range. For example, the sludge concentration and dehydration system described in Patent Document 1 controls the rotation speed of the screw shaft of the dehydrator in order to stably dehydrate a constant flow rate of sludge. In addition, the sludge treatment system described in Patent Document 2 controls the pressing pressure of the back pressure plate and the rotation speed of the screw so that the moisture content of the dehydrated cake is equal to or lower than a certain value. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-030158 A [Patent Document 2] JP 2013-208609 A Summary of the Invention [Problem to be solved by the invention]

[0004] For example, when the dewaterability of the supplied sludge improves, the sludge flow rate increases and the moisture content of the dehydrated cake decreases. In this case, if the screw rotation speed is reduced to maintain the sludge flow rate within a predetermined range as in Patent Document 1, the moisture content of the dehydrated cake further decreases. On the other hand, if the screw rotation speed is increased to maintain the moisture content of the dehydrated cake within a predetermined range as in Patent Document 2, the sludge flow rate further increases.

[0005] Furthermore, when the dewaterability of the supplied sludge deteriorates, the sludge flow rate decreases and the moisture content of the dehydrated cake increases. In this case, if the screw rotation speed is increased to maintain the sludge flow rate within a predetermined range as in Patent Document 1, the moisture content of the dehydrated cake increases further. On the other hand, if the screw rotation speed is decreased to maintain the moisture content of the dehydrated cake within a predetermined range as in Patent Document 2, the sludge flow rate decreases further.

[0006] That is, if the sludge flow rate is to be maintained within a predetermined range, the moisture content of the dehydrated cake will fluctuate greatly, whereas if the moisture content of the dehydrated cake is to be maintained within a predetermined range, the sludge flow rate will fluctuate greatly.

[0007] An object of one aspect of the present invention is to maintain both the flow rate of liquid supplied to a dehydrator and the moisture content of the dehydrated cake discharged from the dehydrator within a predetermined range. [Means for solving the problem]

[0008] In order to solve the above problems, a control device according to one embodiment of the present invention includes an acquisition unit that acquires measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which an agent for coagulating suspended solids is added to the liquid containing suspended solids and is supplied to a screw press type dehydrator that dehydrates the liquid while transporting it; a first prediction unit that uses the measurement data acquired by the acquisition unit to predict the moisture content of a dehydrated cake discharged from the dehydrator at a time when a residence time for the liquid to remain in the dehydrator has elapsed from the time when the measurement data was measured; and a control unit that, when the flow rate of the liquid acquired by the acquisition unit is outside a first predetermined range, controls the rotation speed of the screw so that the flow rate of the liquid is within the first predetermined range, and, when the flow rate of the liquid is within the first predetermined range and the moisture content of the dehydrated cake predicted by the first prediction unit is outside a second predetermined range, controls the rotation speed of the screw so that the moisture content of the dehydrated cake is within the second predetermined range.

[0009] In addition, a control device according to another aspect of the present invention includes an acquisition unit that acquires measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which an agent for coagulating suspended solids is added to the liquid containing suspended solids, and is supplied to a screw press type dehydrator that dehydrates the liquid while transporting it; a first prediction unit that uses the measurement data acquired by the acquisition unit to predict the moisture content of a dehydrated cake discharged from the dehydrator at a time when a residence time for the liquid to remain in the dehydrator has elapsed from the time when the measurement data was measured; a second prediction unit that predicts the time to stop operation of the dehydrator based on the measurement data acquired by the acquisition unit; and a control unit that controls the rotation speed of the screw so that the flow rate of the liquid acquired by the acquisition unit is within a first predetermined range, the moisture content of the dehydrated cake predicted by the first prediction unit is within a second predetermined range, and the predicted time predicted by the second prediction unit is within a third predetermined range.

[0010] In addition, a control method for a control device according to another aspect of the present invention includes an acquisition step of acquiring measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which an agent for coagulating suspended solids is added to the liquid containing suspended solids and supplied to a screw press type dehydrator that dehydrates the liquid while transporting it, a first prediction step of using the measurement data acquired in the acquisition step to predict the moisture content of a dehydrated cake discharged from the dehydrator at a time point after a residence time for the liquid to remain in the dehydrator has elapsed from the time of measurement of the measurement data, and a control step of controlling the rotation speed of the screw if the flow rate of the liquid acquired in the acquisition step is outside a first predetermined range so that the flow rate of the liquid is within the first predetermined range, and controlling the rotation speed of the screw if the flow rate of the liquid is within the first predetermined range and the moisture content of the dehydrated cake predicted in the first prediction step is outside a second predetermined range.

[0011] In addition, a control method for a control device according to another aspect of the present invention includes an acquisition step of acquiring measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which an agent for coagulating suspended solids is added to the liquid containing suspended solids while dewatering the liquid, a first prediction step of predicting, using the measurement data acquired in the acquisition step, a moisture content of a dehydrated cake discharged from the dehydrator at a time when a residence time for the liquid to reside in the dehydrator has elapsed from the time when the measurement data was measured, a second prediction step of predicting a time to stop operation of the dehydrator based on the measurement data acquired in the acquisition step, and a control step of controlling the rotation speed of the screw so that the flow rate of the liquid acquired in the acquisition step is within a first predetermined range, the moisture content of the dehydrated cake predicted in the first prediction step is within a second predetermined range, and the predicted time predicted in the second prediction step is within a third predetermined range. Effect of the Invention

[0012] According to one aspect of the present invention, both the flow rate of liquid supplied to a dehydrator and the moisture content of the dehydrated cake discharged from the dehydrator can be maintained within a predetermined range. [Brief description of the drawings]

[0013] [Figure 1] 2 is a block diagram showing an example of a configuration of a main part of an information processing device in the control system according to one embodiment of the present invention; FIG. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of the control system. [Diagram 3] 10 is a flowchart illustrating an example of a process of issuing an instruction to a control device in the information processing device. [Figure 4] 6 is a graph showing changes over time in various measured values ​​in one embodiment of the information processing device. [Diagram 5] FIG. 11 is a block diagram showing an example of a configuration of a main part of an information processing device in a control system according to another embodiment of the present invention. [Figure 6]10 is a flowchart illustrating an example of a process of issuing an instruction to a control device in the information processing device. [Figure 7] 6 is a graph showing changes over time in various measured values ​​in one embodiment of the information processing device. [Figure 8] FIG. 13 is a block diagram showing an example of a configuration of a main part of an information processing device in a control system according to yet another embodiment of the present invention. [Figure 9] 10 is a graph showing the variation in moisture content estimated values ​​by the estimation model in the information processing device with respect to actual moisture content values ​​measured by an operator. [Figure 10] FIG. 2 is a model diagram showing a concept of creating training data for a prediction model in the information processing device. [Figure 11] 10 is a flowchart showing an example of a process of updating a prediction model and an estimation model in the information processing device. [Figure 12] 13 is a flowchart showing an example of an instruction process to a control device in a control system according to still another embodiment of the present invention. [Figure 13] 5 is a flowchart showing an example of a process of issuing an instruction to a control device in the control system. [Figure 14] FIG. 13 is a block diagram showing an example of a configuration of a main part of an information processing device in a control system according to yet another embodiment of the present invention. [Figure 15] 5 is a flowchart illustrating an example of a process performed by a control unit in the information processing device. [Figure 16] 13 is a flowchart showing an example of a drug rate adjustment process in the process of the control unit. [Figure 17] 13 is a flowchart showing an example of the drug injection rate reduction effect determination process in the drug rate adjustment process. [Figure 18] 13 is a flowchart showing an example of the drug injection rate increase effect determination process in the drug rate adjustment process. [Figure 19] FIG. 13 is a block diagram showing an example of a configuration of a main part of an information processing device in a control system according to yet another embodiment of the present invention. [Figure 20]10 is a flowchart illustrating an example of a process of issuing an instruction to a control device in the information processing device. [Figure 21] 5 is a flowchart illustrating an example of a process performed by a control unit in the information processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, embodiments of the present invention will be described in detail. For the sake of convenience, the same reference numerals will be used to designate members having the same functions as those in the embodiments, and descriptions thereof will be omitted as appropriate.

[0015] [Embodiment 1] An embodiment of the present invention will be described with reference to FIGS.

[0016] [Control System] Fig. 2 is a diagram showing an example of the configuration of a control system 100 according to this embodiment. The control system 100 is a system used in a plant that adds an agent that coagulates suspended solids to a liquid to be treated in a coagulation tank to form flocs, and then performs solid-liquid separation of the liquid to be treated in which the flocs have formed. In the following, an example will be described in which the liquid to be treated is sludge, but the control system 100 can also be applied to plants that treat liquids other than sludge. Incidentally, sludge is a liquid containing fine solids that is generated in wastewater treatment and the like, and can also be called a slurry.

[0017] As will be described in detail below, the control system 100 performs each process of the sludge treatment process from a process of converting the sludge to be treated into flocculated sludge by flocculating suspended solids in the sludge to be treated to form flocs, to a process of dewatering the flocculated sludge to obtain dehydrated sludge (also called dehydrated cake) and dehydrated filtrate. As shown in Fig. 2, the control system 100 includes an information processing device 1, a control device 3, a flocculator 5, and a dehydrator 9.

[0018] The flocculator 5 is a device that adds a chemical agent that flocculates suspended solids to the liquid to be treated in a coagulation tank and moderately stirs the liquid to form flocs. Specifically, the flocculator 5 uses sludge as the liquid to be treated, coagulates suspended solids in the sludge to form flocs, and produces coagulated sludge. The flocculator 5 in FIG. 2 includes a coagulation tank 51, a stirring blade 52, a motor 53, and an inspection window 54. The flocculator 5 also includes a sludge inlet 55, a chemical agent inlet 56, and a discharge outlet 57.

[0019] Furthermore, a photographing device 72 and a lighting device 71 for photographing are attached to the inspection window 54. The photographing device 72 may be any device capable of at least taking still images. It is preferable that the coagulation tank 51 is opaque so that the way light hits the flocs does not change while the control system 100 is in operation. Moreover, it is preferable that the photographing device 72 and the lighting device 71 are housed in a light-shielding dark box with an opening on the inspection window 54 side, as in the illustrated example.

[0020] The dehydrator 9 is a device that performs solid-liquid separation of the liquid to be treated in which flocs are formed. Specifically, the dehydrator 9 is disposed after the flocculator 5, and performs solid-liquid separation by dehydrating the coagulated sludge (liquid) discharged from the flocculator 5. The dehydrator 9 in FIG. 2 is a screw press type dehydrator equipped with an outer body screen 91 and a screw 92. The dehydrator 9 is also provided with a sludge inlet 93, a filtrate outlet 94, and a dehydrated cake outlet 95. Although not shown, the dehydrator 9 also includes a motor for rotating the screw 92. Of course, the dehydrator 9 is not limited to the screw press type as long as it can dehydrate the coagulated sludge. For example, a centrifugal dehydrator, a filter press type dehydrator, a belt press dehydrator, or the like can be applied.

[0021] In the control system 100, the sludge to be treated is continuously or intermittently supplied from a sludge inlet 55 into the coagulation tank 51 of the flocculator 5 by a supply device (not shown). The supply rate of the sludge may be automatically controlled by the supply device or its control device 3 according to the treatment rate of the sludge by the flocculator 5 and the dehydrator 9.

[0022] Then, chemicals (including at least a flocculant) for flocculating the sludge are fed into the sludge in the flocculation tank 51 through chemical inlet 56. In this state, motor 53 is driven to rotate agitator blade 52, which mixes the sludge and chemicals and forms flocs. The flocculated sludge, which is a mixture of the formed flocs and the water contained in the sludge, is discharged from outlet 57.

[0023] Next, this flocculated sludge is supplied into the outer body screen 91 from a sludge inlet 93 of the dewaterer 9. In the dewaterer 9, the flocculated sludge is transported by a screw 92 and dewatered under pressure by the screw 92, and the filtrate is discharged from a filtrate outlet 94, and a dehydrated cake, which is a mass of the dewatered flocculated sludge, is discharged from a dehydrated cake outlet 95.

[0024] The sludge is supplied into the coagulation tank 51 from the sludge inlet 55, and is pushed out and discharged from the outlet 57 of the coagulation tank 51, and the discharged coagulated sludge is supplied to the dehydrator 9. Therefore, the flow rate of the sludge supplied to the coagulation tank 51 and the flow rate of the sludge supplied to the dehydrator 9 match at the same time.

[0025] As will be described in detail below, the information processing device 1 acquires at least any one of measurement data related to the liquid supplied to the coagulation tank 51, measurement data related to the chemicals supplied to the coagulation tank 51, measurement data related to the liquid in the coagulation tank 51, measurement data related to the operation of the coagulation tank 51, and measurement data related to the operation of the dehydrator 9. Then, the information processing device 1 predicts the moisture content of the dehydrated cake based on the acquired measurement data.

[0026] The information processing device 1 can also control the operation of various devices (e.g., the flocculator 5, the dehydrator 9, and a sludge and chemical supply device (not shown)) that are components of the control system 100 via the control device 3. The control device 3 is a device that controls the operation of various devices that are components of the control system 100. The control device 3 may be, for example, a PLC (Programmable Logic Controller). In the example of FIG. 2, the control device 3 includes a flocculator control device 3a that controls devices related to the flocculator 5, and a dehydrator control device 3b that controls devices related to the dehydrator 9.

[0027] [Information processing device] 1 is a block diagram showing an example of a configuration of a main part of an information processing device 1. As shown in the figure, the information processing device 1 includes a control unit 10 that controls each part of the information processing device 1, and a storage unit 11 that stores various data used by the information processing device 1. The information processing device 1 also includes a communication unit 12 that allows the information processing device 1 to communicate with other devices, an input unit 13 that accepts input of various data to the information processing device 1, and an output unit 14 that allows the information processing device 1 to output various data.

[0028] The control unit 10 includes an acquisition unit 101, a prediction unit 102, and an instruction unit 103 (control unit). The instruction unit 103 will be described later in the section "Instruction Unit."

[0029] The storage unit 11 includes a prediction model 111. Details of the prediction model 111 will be described later in the section "About the prediction model."

[0030] The acquiring unit 101 acquires measurement data indicating the flow rate of coagulated sludge supplied to the dehydrator 9. In addition, the acquiring unit 101 acquires at least one of measurement data related to the liquid supplied to the coagulation tank 51, measurement data related to the chemicals supplied to the coagulation tank 51, measurement data related to the liquid in the coagulation tank 51, measurement data related to the operation of the coagulation tank 51, and measurement data related to the operation of the dehydrator 9. Details of each measurement data will be described later in the section "Regarding the prediction model."

[0031] Prediction unit 102 predicts the moisture content of the dehydrated cake from the measurement data acquired by acquisition unit 101, using prediction model 111 stored in memory unit 11. This dehydrated cake is the dehydrated cake discharged from dehydrator 9 at a point in time when the retention time of the flocculated sludge in dehydrator 9 has elapsed from the time of measurement of the measurement data (hereinafter referred to as the "elapsed time point"). Prediction unit 102 executes a prediction using prediction model 111 every time acquisition unit 101 acquires new measurement data. This allows prediction unit 102 to predict the moisture content of the dehydrated cake in real time, that is, continuously at short time intervals (for example, every minute).

[0032] The instruction unit 103 issues various instructions to the control device 3 via the communication unit 12. In this embodiment, when the flow rate of the flocculated sludge acquired by the acquisition unit 101 is outside a first predetermined range, the instruction unit 103 instructs the dehydrator control device 3b to control the rotation speed of the screw 92 so that the flow rate of the flocculated sludge falls within the first predetermined range. Therefore, the first predetermined range corresponds to a predetermined range in which the flow rate of the flocculated sludge is appropriate.

[0033] The upper limit of the first predetermined range may be, for example, the upper limit of the flow rate of the pump that supplies the flocculated sludge to the dehydrator 9. The lower limit of the first predetermined range may be, for example, the lower limit of the flow rate of the pump. By narrowing the first predetermined range, the instruction unit 103 can stabilize the flow rate of the flocculated sludge. By further narrowing the first predetermined range, the instruction unit 103 can cause the dehydrator control device 3b to control the flow rate of the flocculated sludge to be constant.

[0034] Furthermore, when the flow rate of the coagulated sludge is within a first predetermined range and the predicted value of the moisture content of the dehydrated cake predicted by prediction unit 102 is outside a second predetermined range, instruction unit 103 instructs dehydrator control device 3b to control the rotation speed of screw 92 so that the predicted value of the moisture content of the dehydrated cake falls within the second predetermined range. Therefore, the second predetermined range corresponds to a predetermined range in which the moisture content of the dehydrated cake is appropriate. Note that specific instruction processing by instruction unit 103 will be described later in the section "Instruction Processing".

[0035] [About the prediction model] The prediction model 111 is a model of the relationship between the measurement data at the time of measurement acquired by the acquisition unit 101 as an explanatory variable and the moisture content of the dehydrated cake discharged from the dehydrator 9 at an elapsed time point (hereinafter referred to as the "moisture content at the elapsed time point") as an objective variable. For example, a prediction model generated by machine learning using teacher data indicating the correspondence between measurement data measured in the past and the moisture content corresponding to the measurement data can be used. The algorithm of the prediction model 111 is not particularly limited, and for example, a prediction model such as a regression or multiple regression model, a neural network, or a random forest can be used.

[0036] The measurement data acquired by the acquisition unit 101 and used for prediction by the prediction model 111 includes the following:

[0037] (1) Measurement data regarding the sludge supplied to the coagulation tank 51. The measurement data is, for example, at least one of the supply flow rate of the sludge per unit time and the concentration of the sludge, and is measured before the sludge inlet 55.

[0038] (2) Measurement data related to the chemical agent supplied to the coagulation tank 51. The measurement data is, for example, the supply flow rate of the chemical agent per unit time, and is measured before the chemical agent inlet 56.

[0039] (3) Measurement data on the sludge in the coagulation tank 51. The measurement data is at least one of the average gray value of the flocs and the average unit area of ​​the gaps between the flocs, and is obtained by image processing of still images taken by the photographing device 72. The average gray value is an index of the sludge color tone (light and dark). The average unit area is an index of the floc diameter.

[0040] (4) Measurement data related to the operation of the coagulation tank 51. The measurement data is the rotation speed of the agitator blades 52 in the coagulation tank 51, and is acquired from the flocculator control device 3a.

[0041] (5) Measurement data related to the operation of the dehydrator 9. The measurement data is at least any one of the operation time of the dehydrator 9, the rotation speed of the screw 92 of the dehydrator 9, the supply flow rate of the coagulated sludge to the dehydrator 9 per unit time, and the feeding pressure of the coagulated sludge fed to the dehydrator 9, and is acquired from the dehydrator control device 3 b.

[0042] In this embodiment, various measurement data can be adopted as shown in (1) to (5) above. Therefore, the moisture content of the dehydrated cake can be predicted with high accuracy by using multifaceted explanatory variables. Among the measurement data shown in (1) to (5) above, the measurement data that have a large contribution to the prediction accuracy of the prediction model 111 include the operation time, the rotation speed of the screw 92, and the supply flow rate shown in (5) above, and the average floc shading value shown in (3) above.

[0043] According to the above configuration, when the flow rate of the flocculated sludge supplied to the dehydrator 9 is outside the first predetermined range, the control unit 10 first controls the rotation speed of the screw 92 so that the flow rate of the flocculated sludge falls within the first predetermined range. This makes it possible to maintain the flow rate of the flocculated sludge within the first predetermined range.

[0044] At this time, there is a possibility that the moisture content of the dehydrated cake will deviate from the second predetermined range due to the change in the rotation speed of the screw 92. However, the time when the moisture content of the dehydrated cake actually deviates from the second predetermined range is the time when the retention time has elapsed from the time when the flow rate of the flocculated sludge is measured.

[0045] Therefore, when the prediction unit 102 next predicts the moisture content of the dehydrated cake, if the flow rate of the flocculated sludge is within the first predetermined range and the moisture content of the dehydrated cake is outside the second predetermined range, the control unit 10 controls the rotation speed of the screw 92 so that the moisture content of the dehydrated cake falls within the second predetermined range. This makes it possible to maintain the moisture content of the dehydrated cake within the second predetermined range when the retention time has elapsed since the measurement of the flow rate of the flocculated sludge.

[0046] [Instruction Processing] 3 is a flowchart showing an example of an instruction process (control method) to the control device 3 in the information processing device 1 having the above configuration. This instruction process is executed periodically (for example, every 5 minutes). As shown in FIG. 3, first, the acquisition unit 101 collects (acquires) various measurement data (S11). Next, the prediction unit 102 predicts, using a prediction model 111, from the measurement data, the moisture content of the dehydrated cake discharged from the dehydrator 9 at the time when the residence time has elapsed from the time when the measurement data was measured (S12).

[0047] Next, the instruction unit 103 determines whether the flow rate of flocculated sludge supplied to the dehydrator 9, which is included in the measurement data, is smaller than a first predetermined range, is within the first predetermined range, or is larger than the first predetermined range (S13).

[0048] If the flow rate of the flocculated sludge is less than the first predetermined range in step S13, the process proceeds to step S15. On the other hand, if the flow rate of the flocculated sludge is greater than the first predetermined range in step S13, the process proceeds to step S16.

[0049] On the other hand, if the flow rate of the flocculated sludge is within the first predetermined range in step S13, the instruction unit 103 determines whether the predicted value of the moisture content of the dehydrated cake at the elapsed time point predicted in step S12 is smaller than the second predetermined range, is within the second predetermined range, or is larger than the second predetermined range (S14).

[0050] If the predicted value is smaller than the second predetermined range in step S14, the process proceeds to step S15. On the other hand, if the predicted value is larger than the second predetermined range in step S14, the process proceeds to step S16. On the other hand, if the predicted value is within the second predetermined range in step S14, the instructing unit 103 determines that both the flocculated sludge flow rate and the predicted value are within appropriate ranges, and ends the instruction process.

[0051] In step S15, the instruction unit 103 instructs the dehydrator control device 3b to increase the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount (for example, 0.01 revolutions / minute). Thereafter, the instruction process is terminated. By periodically repeating steps S11 to S13 and S15, the flow rate of the flocculated sludge increases stepwise and can finally be brought into the first predetermined range. Furthermore, by periodically repeating steps S11 to S14 and S15, the predicted value of the moisture content of the dehydrated cake at the elapsed time point increases stepwise and can finally be brought into the second predetermined range.

[0052] In step S16, the instruction unit 103 instructs the dehydrator control device 3b to reduce the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount. Thereafter, the instruction process is terminated. By periodically repeating steps S11 to S13 and S16, the flow rate of the flocculated sludge can be reduced stepwise and finally brought into the first predetermined range. Furthermore, by periodically repeating steps S11 to S14 and S16, the predicted value of the moisture content of the dehydrated cake at the elapsed time point can be reduced stepwise and finally brought into the second predetermined range.

[0053] [Modifications] The execution entity of each process described in the above embodiment is arbitrary and is not limited to the above example. For example, each step of the moisture content prediction method shown in Fig. 3 can be shared among multiple information processing devices. In other words, the moisture content prediction method may be executed by one information processing device 1 or may be executed by multiple information processing devices.

[0054] [Additional Notes] In the above embodiment, the prediction unit 102 predicts the moisture content of the dehydrated cake from the measurement data using the learned prediction model 111, but the present invention is not limited to this. For example, the prediction unit 102 may predict the moisture content of the dehydrated cake from the measurement data based on a predetermined calculation formula.

[0055] [Example] Fig. 4 is a graph showing the time variations of various measured values ​​in one embodiment of the information processing device 1 having the above configuration. The horizontal axis of Fig. 4 is the operating time (minutes). The vertical axis of Fig. 4 is the measured value of each measurement data, and each measurement data is shown on an arbitrary scale. The measured values ​​in Fig. 4 are the dewaterability of the supplied flocculated sludge, the flow rate of the flocculated sludge, the moisture content of the dehydrated cake, and the rotation speed of the screw 92.

[0056] In Fig. 4, this embodiment is shown by a solid line, and in Fig. 4, a comparative example in which the rotation speed of the screw 92 is controlled based on the water content is shown by a dashed line.

[0057] 4, when the dewaterability of the flocculated sludge decreases, the moisture content of the dewatered cake increases after the retention time has elapsed. Therefore, in the comparative example, the rotation speed of the screw 92 is gradually decreased. However, in this case, the flow rate of the flocculated sludge is significantly decreased.

[0058] In contrast, in this embodiment, the amount of reduction in the rotational speed of the screw 92 is reduced so that the flow rate of the coagulated sludge falls within a first predetermined range. This makes it possible to prevent a large reduction in the flow rate of the coagulated sludge. Then, in this embodiment, once the flow rate of the coagulated sludge falls within the first predetermined range, the amount of reduction in the rotational speed of the screw 92 is maintained so that the moisture content of the dehydrated cake falls within a second predetermined range. This makes it possible to prevent a large increase in the moisture content of the dehydrated cake.

[0059] 4, when the dewaterability of the flocculated sludge increases, the moisture content of the dewatered cake after the retention time has elapsed decreases. Therefore, in the comparative example, the rotation speed of the screw 92 is increased stepwise. However, in this case, the flow rate of the flocculated sludge increases significantly.

[0060] In contrast, in this embodiment, the increase in the rotational speed of the screw 92 is reduced so that the flow rate of the flocculated sludge falls within a first predetermined range. This makes it possible to prevent a significant decrease in the flow rate of the flocculated sludge. Then, in this embodiment, once the flow rate of the flocculated sludge falls within the first predetermined range, the increase in the rotational speed of the screw 92 is maintained so that the moisture content of the dehydrated cake falls within a second predetermined range. This makes it possible to prevent a significant decrease in the moisture content of the dehydrated cake.

[0061] [Embodiment 2] Another embodiment of the present invention will be described with reference to Fig. 5 and Fig. 6. A control system 100 according to this embodiment is different from the control system 100 shown in Fig. 2 in the configuration of the information processing device 1, but the other configurations are similar.

[0062] Fig. 5 is a block diagram showing an example of a configuration of a main part of the information processing device 1 of this embodiment. The information processing device 1 of this embodiment differs from the information processing device 1 shown in Fig. 1 in that the name of the prediction unit 102 has been changed to a first prediction unit 102, that the control unit 10 further includes a second prediction unit 104, and that an instruction unit 105 (control unit) is provided instead of the instruction unit 103, but the other configurations are the same.

[0063] Incidentally, for efficient sludge treatment, it is desirable to predict when the total amount of treatment in the dehydrator 9, such as the flow rate of the coagulated sludge and the weight of the dehydrated cake, will reach a target value for one day and when the operation of the dehydrator 9 will be terminated. In this case, the operator can carry out treatment without delay after the operation of the dehydrator 9 is terminated.

[0064] Therefore, in this embodiment, the second prediction unit 104 predicts the operation stop time te at which the operation of the dehydrator 9 is stopped, based on the measurement data acquired by the acquisition unit 101.

[0065] Specifically, the second prediction unit 104 first acquires a target value DAt of the throughput of the dehydrator 9. The second prediction unit 104 also acquires a first period T1 from operation start time t0 when the dehydrator 9 starts operation to a first time t1, a measured value A1 of the throughput per unit rotation of the screw 92 during the first period T1, and a measured value rr1 of the rotation speed of the screw 92 at the first time t1. The throughput may be, for example, the amount of coagulated sludge supplied to the dehydrator 9 or the amount of dehydrated cake discharged from the dehydrator 9.

[0066] Next, the second prediction unit 104 acquires a measurement value A1 of the throughput per unit rotation of the screw 92 in the first period T1, which is an average value PA1 of the measurement values ​​of the throughput per unit rotation of the screw 92 for a predetermined number of past days. The second prediction unit 104 also acquires a measurement value PA2 of the throughput per unit rotation of the screw 92 for the operation period Top from the operation start time t0 to the operation stop time te, which is an average value PA2 of the measurement values ​​of the throughput for the predetermined number of past days.

[0067] Next, the second prediction unit 104 predicts the operating period Top from the target value DAt of the throughput to be reached in the operating period Top based on the following equation (1) using the measured value A1 of the throughput per unit rotation of the screw 92 in the first period T1, the average value PA1 of the measured values ​​of the throughput per unit rotation of the screw 92 in the first period T1 in the specified number of past days, the average value PA2 of the measured values ​​of the throughput per unit rotation of the screw 92 at the operating period Top in the specified number of past days, and the measured value rr1 of the rotational speed of the screw 92 at the first time t1. DAt / Top=A1×(PA2 / PA1)×rr1 ····(1). Then, the second prediction unit 104 outputs a predicted value of the operation stop time te by adding the operation start time t0 to the predicted value of the operation period Top. Note that the second prediction unit 104 may predict the operation stop time te based on the measurement data acquired by the acquisition unit 101 using a known method.

[0068] The instruction unit 105 issues various instructions to the control device 3 via the communication unit 12. In this embodiment, similar to the instruction unit 103 shown in Fig. 1, when the flow rate of the flocculated sludge acquired by the acquisition unit 101 is outside a first predetermined range, the instruction unit 105 instructs the dehydrator control device 3b to control the rotation speed of the screw 92 so that the flow rate of the flocculated sludge falls within the first predetermined range. Therefore, the first predetermined range corresponds to a predetermined range in which the flow rate of the flocculated sludge is appropriate.

[0069] Furthermore, when the flow rate of the flocculated sludge is within the first predetermined range and the predicted time of operation shutdown predicted by the second prediction unit 104 is outside the third predetermined range, the instruction unit 105 instructs the dehydrator control device 3b to control the rotation speed of the screw 92 so that the predicted time falls within the third predetermined range. Therefore, the third predetermined range corresponds to a predetermined range in which the time of operation shutdown is appropriate.

[0070] Furthermore, when the flow rate of the flocculated sludge is within a first predetermined range, the predicted time of operation shutdown is within a third predetermined range, and the predicted value of the moisture content of the dehydrated cake predicted by first prediction unit 102 is outside the second predetermined range, instructing unit 103 to control the rotation speed of screw 92 so that the predicted value of the moisture content of the dehydrated cake falls within the second predetermined range. Therefore, the second predetermined range corresponds to a predetermined range in which the moisture content of the dehydrated cake is appropriate.

[0071] When the flow rate of the flocculated sludge is within the first predetermined range and the moisture content of the dehydrated cake is outside the second predetermined range, the control unit 10 controls the rotation speed of the screw 92 so that the moisture content of the dehydrated cake falls within the second predetermined range. At this time, by changing the rotation speed of the screw 92, the flow rate of the flocculated sludge may change within the first predetermined range, and the time at which the amount of the flocculated sludge or the dehydrated cake reaches a target value may change. As a result, the time at which the operation of the dehydrator 9 is stopped may change.

[0072] Therefore, in this embodiment, the control unit 10 predicts the time to stop the operation of the dehydrator 9 based on the measurement data, and when the predicted time of operation stop is outside the third predetermined range, the control unit 10 controls the rotation speed of the screw 92 so that the predicted time falls within the third predetermined range. In addition, when the flow rate of the flocculated sludge is within the first predetermined range, the predicted time is within the third predetermined range, and the moisture content of the dehydrated cake is outside the second predetermined range, the control unit 10 controls the rotation speed of the screw 92 so that the moisture content of the dehydrated cake falls within the second predetermined range. This may cause a large change in the moisture content of the dehydrated cake, but the predicted time of operation stop can be maintained within the third predetermined range. As a result, the operation of the dehydrator 9 can be stopped as scheduled, and the process after the operation of the dehydrator 9 is stopped, such as the transportation of the dehydrated cake, can be performed as scheduled.

[0073] Fig. 6 is a flowchart showing an example of an instruction process (control method) for the control device 3 in the information processing device 1 having the above configuration. The instruction process of this embodiment differs from the instruction process shown in Fig. 3 in that step S21 is provided between step S12 and step S13 and step S22 is provided between step S13 and step S14, but the other processes are the same.

[0074] In step S21, second prediction unit 104 predicts the time to stop operation of dehydrator 9 based on the above-mentioned measurement data. Note that either step S12 or step S21 may be processed first, or they may be processed simultaneously.

[0075] In step S22, if the flow rate of the flocculated sludge is within a first predetermined range in step S13, the instruction unit 103 determines whether the predicted time of the operation shutdown predicted in step S21 is later than a third predetermined range, within the third predetermined range, or earlier than the third predetermined range.

[0076] If the predicted value is later than the third predetermined range in step S22, proceed to step S15. On the other hand, if the predicted value is earlier than the third predetermined range in step S22, proceed to step S16. On the other hand, if the predicted value is within the third predetermined range in step S22, proceed to step S14.

[0077] Therefore, if the predicted value is within the second predetermined range in step S14, the instruction unit 103 determines that the flow rate of the flocculated sludge, the predicted time, and the predicted value are all within the appropriate range, and ends the instruction process. Furthermore, by periodically repeating steps S11, S12, S21, S13, S22, and S15, the predicted time of the operation shutdown can be increased stepwise and finally brought into the third predetermined range. Furthermore, by periodically repeating steps S11, S12, S21, S13, S22, and S16, the predicted time of the operation shutdown can be decreased stepwise and finally brought into the third predetermined range.

[0078] [Example] Fig. 7 is a graph showing the time changes of various measured values ​​in one embodiment of the information processing device 1 having the above configuration. The horizontal axis of Fig. 7 is the operation time (minutes). The vertical axis of Fig. 7 is the measured value of each measurement data, and each measurement data is shown on an arbitrary scale. The measured values ​​in Fig. 7 are the dewaterability of the supplied flocculated sludge, the lag in the operation stop time, the flow rate of the flocculated sludge, the moisture content of the dewatered cake, and the rotation speed of the screw 92.

[0079] In Fig. 7, this embodiment is shown by a solid line, and in Fig. 7, a comparative example in which the rotation speed of the screw 92 is controlled based on the water content is shown by a dashed line.

[0080] 7, when the dewaterability of the flocculated sludge decreases, the moisture content of the dewatered cake increases after the retention time has elapsed. Therefore, in the comparative example, the rotation speed of the screw 92 is gradually decreased. However, in this case, the predicted time of operation shutdown is significantly delayed, and the flow rate of the flocculated sludge is significantly decreased.

[0081] In contrast, in this embodiment, the amount of reduction in the rotational speed of the screw 92 is reduced so that the flow rate of the coagulated sludge falls within a first predetermined range. This makes it possible to prevent a large reduction in the flow rate of the coagulated sludge. Furthermore, in this embodiment, when the flow rate of the coagulated sludge falls within the first predetermined range, the rotational speed of the screw 92 is increased so that the predicted time of operation shutdown falls within a third predetermined range. This makes it possible to prevent the predicted time of operation shutdown from being significantly delayed.

[0082] In this embodiment, when the flow rate of the flocculated sludge falls within the first predetermined range and the predicted time of operation shutdown falls within the third predetermined range, the amount of reduction in the rotational speed of the screw 92 is maintained so that the moisture content of the dehydrated cake falls within the second predetermined range. This makes it possible to prevent the moisture content of the dehydrated cake from increasing significantly.

[0083] 7, when the dewaterability of the flocculated sludge increases, the moisture content of the dewatered cake after the retention time has elapsed decreases. Therefore, in the comparative example, the rotation speed of the screw 92 is increased stepwise. However, in this case, the predicted time of operation shutdown becomes significantly earlier, and the flow rate of the flocculated sludge increases significantly.

[0084] In contrast, in this embodiment, the increase in the rotational speed of the screw 92 is reduced so that the flow rate of the coagulated sludge falls within a first predetermined range. This makes it possible to prevent a large increase in the flow rate of the coagulated sludge. Furthermore, in this embodiment, when the flow rate of the coagulated sludge falls within the first predetermined range, the rotational speed of the screw 92 is reduced so that the predicted time of operation shutdown falls within a third predetermined range. This makes it possible to prevent the predicted time of operation shutdown from being significantly earlier.

[0085] In this embodiment, when the flow rate of the flocculated sludge falls within the first predetermined range and the predicted time of operation shutdown falls within the third predetermined range, the increase in the rotational speed of the screw 92 is maintained so that the moisture content of the dehydrated cake falls within the second predetermined range. This makes it possible to prevent the moisture content of the dehydrated cake from decreasing significantly.

[0086] [Additional Notes] Any of steps S13, S22, and S14 may be processed first. That is, the instruction unit 105 may instruct the dehydrator control device 3b to control the rotation speed of the screw 92 so that the flow rate of the flocculated sludge acquired by the acquisition unit 101 is within a first predetermined range, the predicted value of the moisture content of the dehydrated cake predicted by the first prediction unit 102 is within a second predetermined range, and the predicted time of operation shutdown predicted by the second prediction unit 104 is within a third predetermined range.

[0087] In this case, the dehydrator 9 can be operated while maintaining the flow rate of the coagulated sludge and the moisture content of the dehydrated cake within appropriate ranges, and the operation of the dehydrator 9 can be stopped as scheduled, so that processing after the operation of the dehydrator 9 is stopped, such as transporting the dehydrated cake, can be carried out as scheduled.

[0088] [Embodiment 3] Yet another embodiment of the present invention will be described with reference to Fig. 8 to Fig. 11. A control system 100 according to this embodiment differs from the control system 100 shown in Fig. 2 in the configuration of an information processing device 1, but the other configurations are similar.

[0089] Fig. 8 is a block diagram showing an example of a configuration of a main part of the information processing device 1 of this embodiment. The information processing device 1 of this embodiment is different from the information processing device 1 shown in Fig. 1 in that the storage unit 11 further includes an estimation model 112 and is further provided with an update unit 106, but the other configurations are the same.

[0090] [About the estimation model] In this embodiment, the moisture content at an elapsed time point, which is the objective variable of prediction model 111, is an estimated value by estimation model 112. Estimation model 112 is an estimation model trained using measurement data related to the operation of dehydrator 9, among the measurement data acquired by acquisition unit 101, as an explanatory variable, and the moisture content of the dehydrated cake discharged from dehydrated cake discharge outlet 95 of dehydrator 9 at the time point of measurement of the measurement data (hereinafter referred to as "moisture content at the time of measurement") as an objective variable.

[0091] The measurement data includes at least one of the following: the operation time of the dehydrator 9, the rotation speed of the screw of the dehydrator 9, the drive current value or torque value of the screw, the back pressure by a back pressure plate provided at the dehydrated cake discharge port 95 (discharge section) of the dehydrator 9 for squeezing liquid, and the opening between the back pressure plate and the dehydrated cake discharge port 95, and is acquired from the dehydrator control device 3b. Among these, the measurement data that contributes greatly to the estimation accuracy of the estimation model 112 include the drive current value of the screw and the opening (particularly when the dehydrator 9 is controlled so that the back pressure is constant). The moisture content is manually analyzed and measured (actually measured) by an operator using a device outside the control system 100. For this reason, the measurement cannot be performed frequently.

[0092] FIG. 9 is a graph showing the variation of the moisture content estimated by the estimation model 112 with respect to the moisture content measured by the operator. In the example of FIG. 9, the explanatory variables are the operation time of the dehydrator 9, the rotation speed and driving current value of the screw of the dehydrator 9, the back pressure by the back pressure plate, and the opening degree between the back pressure plate and the dehydrated cake discharge port 95. Referring to FIG. 9, it can be seen that the variation is extremely small. Therefore, by using the measurement data related to the operation of the dehydrator 9 for the estimation model 112, the moisture content at the time of measurement can be accurately and frequently estimated. As a result, the moisture content of the dehydrated cake can be accurately predicted without increasing the burden on the operator in manually analyzing the moisture content of the dehydrated cake.

[0093] [How to train a predictive model] Next, a description will be given of a method for learning the moisture content by the prediction model 111 of this embodiment. As described above, the prediction model 111 is a model that predicts the moisture content at a future time point from the measurement time point using measurement data at the measurement time point.

[0094] Fig. 10 is a model diagram showing the concept of creating training data for the prediction model 111. The horizontal axis of Fig. 10 is driving time (minutes). The vertical axis of Fig. 10 is the measured value of each measurement data, and each measurement data is shown on an arbitrary scale.

[0095] The measurement data at the measurement time, which are the explanatory variables of the prediction model 111, are the supply flow rate per unit time of the liquid (sludge), the concentration of the liquid (sludge), the average color value of the flocs, the average unit area of ​​the gaps between the flocs, the rotation speed of the agitator blades in the coagulation tank 51, the operation time of the dehydrator 9, the rotation speed of the screw of the dehydrator 9, and the feeding pressure of the liquid (coagulated sludge) fed into the dehydrator 9, as shown in the upper part of FIG. 10.

[0096] The objective variable of the prediction model 111 is the moisture content at the time point. When using an actual measurement value by an operator as this moisture content, there is an upper limit to the number of times an operator can measure in one day, as shown by the white circle in the lower part of Fig. 10. This limits the amount of training data, which is a combination of explanatory variables and objective variables, and as a result, it is difficult to create a highly accurate prediction model.

[0097] Therefore, in this embodiment, instead of actual measurements by an operator, estimated values ​​by the estimation model 112 are used as the objective variables of the training data. As a result, as shown by the gray circles in the lower part of Fig. 10, the number of objective variables is not limited by the number of measurements that an operator can make, so that the amount of training data can be increased and a highly accurate prediction model 111 can be created.

[0098] Incidentally, the estimated value of the moisture content at the above-mentioned elapsed time point is calculated from the measurement data at the above-mentioned elapsed time point by using the estimation model 112. Therefore, for learning the prediction model 111, the measurement data at the measurement time point, which is the explanatory variable of the prediction model 111, and the measurement data at the elapsed time point, which is the explanatory variable of the estimation model 112, are used.

[0099] [Method of predicting moisture content using a prediction model] The prediction unit 102 predicts the moisture content of the dehydrated cake using the learned prediction model 111. That is, the prediction unit 102 inputs at least one of the following explanatory variables into the prediction model 111: measurement data on the liquid supplied to the coagulation tank 51, measurement data on the chemicals supplied to the coagulation tank 51, measurement data on the liquid in the coagulation tank 51, measurement data on the operation of the coagulation tank 51, and measurement data on the operation of the dehydrator 9, thereby predicting the moisture content of the dehydrated cake at the completion of dehydration, which is the objective variable.

[0100] At this time, the acquisition unit 101 may omit acquisition of measurement data that is an explanatory variable of the estimation model 112 but is not an explanatory variable of the prediction model 111, since the prediction unit 102 does not use the measurement data. However, for the processing of the update unit 106 described later, it is desirable for the acquisition unit 101 to perform the above acquisition.

[0101] [About the update section] The update unit 106 performs a process of updating the prediction model 111 and the estimation model 112 during a period when the flocculation tank 51 and the dehydrator 9 are stopped (operation suspension period). Specifically, the update unit 106 updates the estimation model 112 during the operation suspension period by using, as teacher data, a pair of the measurement data acquired by the acquisition unit 101 during the operation period of the dehydrator 9 and the moisture content of the dehydrated cake actually measured by an operator.

[0102] Next, the update unit 106 updates the prediction model during the above-mentioned operation shutdown period using as training data a pair of the measurement data acquired by the acquisition unit 101 during the operation period of the coagulation tank 51 and the dehydrator 9 and an estimate by the estimation model 112 for the moisture content of the dehydrated cake discharged from the dehydrator 9 at the point in time when the retention time has elapsed since the time when the measurement data was measured.

[0103] Typically, the operating period is a set period in one day. Therefore, the update unit 106 performs update once a day. Also, it takes about one day for an operator to actually measure the moisture content of the dehydrated cake. For this reason, the estimation model 112 may be updated using measurement data from the operating period two days ago. On the other hand, it is desirable to update the prediction model 111 using measurement data from the latest operating period.

[0104] Therefore, since the prediction model 111 is updated using the latest measurement data, it is possible to adapt the prediction using the prediction model 111 to the latest conditions of the coagulation tank 51 and the dehydrator 9. Similarly, since the estimation model 112 is updated using the latest measurement data and the actual measurements by the operator, it is possible to adapt the estimation using the estimation model 112 to the latest conditions of the dehydrator 9.

[0105] [Update process] 11 is a flowchart showing an example of the process of updating the prediction model 111 and the estimation model 112 in the information processing device 1. This update process is executed for each operation shutdown period, as described above.

[0106] 11, first, the acquisition unit 101 determines whether or not a new actual measurement value of the moisture content has been acquired by an operator (S31). If the actual measurement value has not been newly acquired (NO in S31), the process proceeds to step S34. On the other hand, if the actual measurement value has been newly acquired (YES in S31), the update unit 106 creates a pair of the newly acquired actual measurement value of the moisture content and the measurement data at the time of the actual measurement value as new teacher data (S32), and updates the estimation model 112 using the created teacher data (S33).

[0107] Next, the update unit 106 uses the estimation model 112 to calculate an estimate of the moisture content during the latest operating period from the measurement data during that period (S34). Next, the update unit 106 creates, for each measurement time point during the latest operating period, a pair of the measurement data at that measurement time point and the above-mentioned estimate value at a time point when the retention time has elapsed since the above-mentioned measurement time point as new teacher data (S35). The update unit 106 then updates the prediction model 111 using the created teacher data (S36). Thereafter, the update process ends.

[0108] (Additional Notes) The update unit 106 and the estimation model 112 in this embodiment may be applied to the information processing device 1 shown in Fig. 5. In this case, the same effects as those of this embodiment can be achieved.

[0109] [Embodiment 4] Yet another embodiment of the present invention will be described with reference to Fig. 12 and Fig. 13. A control system 100 according to this embodiment is different from the control system 100 shown in Fig. 2 in that an operation of issuing an alarm is added to the instruction unit 105 of the information processing device 1 shown in Fig. 5, but the other configurations are similar.

[0110] Specifically, the instruction unit 105 instructs the output unit 14 to issue an alarm if the flow rate of the flocculated sludge is outside a first predetermined range and the predicted value of the moisture content of the dehydrated cake is outside a fourth predetermined range including the second predetermined range. Furthermore, the instruction unit 105 instructs the output unit 14 to issue an alarm if the predicted time predicted by the second prediction unit 104 is outside a fifth predetermined range including the third predetermined range. This makes it possible to alert the worker.

[0111] 12 and 13 are flowcharts showing an example of an instruction process (control method) for the control device 3 in the information processing device 1 having the above configuration. The instruction process of this embodiment differs from the instruction process shown in Fig. 6 in that steps S41, S42, S45, S46, and S49 are provided instead of step S15, and steps S43, S44, S47, S48, and S50 are provided instead of step S16, but the other processes are the same.

[0112] As shown in FIG. 12, in step S13, if the flow rate of the coagulated sludge is smaller than the first predetermined range, the instruction unit 105 instructs the dehydrator control device 3b to increase the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount, as in step S15 (S41). Next, if the predicted value of the moisture content of the dehydrated cake is larger than a fourth predetermined range including the second predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm because the predicted value is too large (S42). In addition, if the predicted time of the operation stop is earlier than a fifth predetermined range including the third predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm because the predicted time is too early (S42). Then, the instruction process ends.

[0113] On the other hand, if the flow rate of the flocculated sludge is greater than the first predetermined range in step S13, the instruction unit 105 instructs the dehydrator control device 3b to reduce the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount, as in step S16 (S43). Next, if the predicted value of the moisture content of the dehydrated cake is smaller than the fourth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm because the predicted value is too small (S44). Furthermore, if the predicted time of the operation stop is later than the fifth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm because the predicted time is too late (S44). Thereafter, the instruction process ends.

[0114] 13, in step S22, if the predicted value is slower than the third predetermined range, the instruction unit 105 instructs the dehydrator control device 3b to increase the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount, as in step S15 (S45). Next, if the predicted value of the moisture content of the dehydrated cake is greater than the fourth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm since the predicted value is too large (S46). Then, the instruction process ends.

[0115] On the other hand, in step S22, if the predicted value is faster than the third predetermined range, the instruction unit 105 instructs the dehydrator control device 3b to reduce the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount, as in step S16 (S47). Next, if the predicted value of the moisture content of the dehydrated cake is smaller than the fourth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm since the predicted value is too small (S48). Then, the instruction process ends.

[0116] 13, if the predicted value is smaller than the second predetermined range in step S14, the instruction unit 105 instructs the dehydrator control device 3b to increase the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount (S49), as in step S15. Then, the instruction process ends.

[0117] On the other hand, if the predicted value is greater than the second predetermined range in step S14, the instruction unit 105 instructs the dehydrator control device 3b to reduce the rotation speed of the screw 92 of the dehydrator 9 by a predetermined amount, as in step S16 (S50). Then, the instruction process is terminated.

[0118] [Embodiment 5] Yet another embodiment of the present invention will be described with reference to Fig. 14 to Fig. 18. A control system 100 according to this embodiment differs from the control system 100 shown in Fig. 2 in the configuration of an information processing device 1, but the other configurations are similar.

[0119] Fig. 14 is a block diagram showing an example of a main configuration of the information processing device 1 of this embodiment. The information processing device 1 of this embodiment is different from the information processing device 1 shown in Fig. 1 in that an adjustment unit 107 (medication control unit) is further provided, and other configurations are similar.

[0120] The adjustment unit 107 adjusts the mode of addition of the chemical based on a first predicted value predicted by the prediction unit 102 using first measurement data related to the properties of the liquid after the addition of the chemical, and a second predicted value predicted by the prediction unit 102 using second measurement data related to the properties of the liquid after the mode of addition of the chemical has been changed. The adjustment unit 107 instructs the flocculator control device 3a (chemical control unit) to add the chemical according to the adjusted mode. This makes it possible to appropriately adjust the mode of addition of the chemical to be added to the liquid containing suspended solids to flocculate the suspended solids.

[0121] [Method of adjusting the mode of drug addition] The adjustment unit 107 adjusts the mode of drug addition based on the first predicted value and the second predicted value predicted by the prediction unit 102. The mode of drug addition means how the drug is added. For example, changing or adjusting at least one of the drug injection rate, the amount of drug added, and the drug supply flow rate corresponds to changing or adjusting the mode of drug addition. In addition, changing the type or composition of the drug to be added also corresponds to changing the mode of drug addition.

[0122] Fig. 15 is a flowchart showing an example of the process of the control unit 10 in the information processing device 1 having the above-described configuration. As shown in Fig. 15, first, the control unit 10 resets and starts the first timer t1 and the second timer t2 (S61).

[0123] Next, the control unit 10 judges whether the second timer t2 has elapsed the second set time (for example, 15 minutes) (S62). If the second timer t2 has elapsed the second set time (YES in S62), the adjustment unit 107 performs an adjustment process of the drug injection rate (S63). The adjustment process of the drug rate will be described later. Then, the process returns to step S61.

[0124] On the other hand, if the second timer t2 has not elapsed the second set time (NO in S62), the control unit 10 determines whether the first timer t1 has elapsed the first set time (e.g., 5 minutes) (S64). If the first timer t1 has not elapsed the first set time (NO in S64), the process returns to step S62.

[0125] On the other hand, if the first timer t1 has elapsed the first set time (YES in S64), the instruction unit 103 performs the instruction process shown in Fig. 3 (S65). Next, the control unit 10 resets and starts the first timer t1 (S66). Then, the process returns to step S62.

[0126] As a result, for example, instruction processing is performed 5 minutes and 10 minutes after the start, and drug injection rate adjustment processing is performed 15 minutes later, and these operations are repeated thereafter. That is, the instruction processing and the drug injection rate adjustment processing are performed alternately. This makes it possible to prevent the execution of the instruction processing from affecting the drug injection rate adjustment processing.

[0127] Fig. 16 is a flow chart showing an example of the drug rate adjustment process. At the start of the process in Fig. 16, the drug is added to the liquid in the flocculator 5 at a predetermined drug injection rate. First, the adjustment unit 107 performs a drug injection rate reduction effect determination process (S71).

[0128] 17 is a flow chart showing an example of the drug injection rate reduction effect judgment process. First, the prediction unit 102 predicts the water content (S81). More specifically, the prediction unit 102 calculates a first predicted value using first measurement data related to the properties of the liquid after the addition of the drug at the time of performing the process of S81.

[0129] Next, the adjustment unit 107 reduces the drug injection rate (S82). The reduction amount of the drug injection rate may be determined in advance. Next, the prediction unit 102 predicts the water content from the measurement data measured after the drug injection rate is reduced in S82. More specifically, the prediction unit 102 calculates a second predicted value using second measurement data related to the properties of the liquid after the mode of drug addition is changed by the process of S82. Note that the second measurement data is measured after a sufficient time has passed since the drug injection rate was reduced in S82 for the effect of the reduction to appear in the measurement data. Hereinafter, this time will be referred to as Δt.

[0130] Next, the adjustment unit 107 returns the drug injection rate to the value before it was reduced in S82 (S84). Next, the prediction unit 102 predicts the water content from the measurement data measured after the drug injection rate was returned in S84 (S85). More specifically, the prediction unit 102 calculates a third predicted value using third measurement data related to the properties of the liquid after the drug addition state is returned to the state immediately before S82 by the process of S84. Thereafter, the process of FIG. 17 ends, and the process returns to the original process of FIG. 16, and proceeds to step S72.

[0131] As with the second measurement data, the third measurement data is also measured after a sufficient time has elapsed for the effect of changing the drug injection rate to appear in the measurement data, which may be the same time (Δt) as that of the second measurement data.

[0132] In step S72, the adjustment unit 107 judges whether the predicted value of the water content has decreased or remained unchanged by the adjustment to decrease the drug injection rate based on the first to third predicted values ​​calculated in S71 (S72). Note that, since the water content usually increases when the drug injection rate is decreased, the judgment result in S72 is often NO. However, for example, if the drug injection rate at the start of the processing in FIG. 16 is too high, the predicted value of the water content may decrease by the adjustment to decrease the drug injection rate. In such a case, the judgment result in S72 is YES.

[0133] If the predicted value is decreased or unchanged in step S72 (YES in S72), the adjustment unit 107 adjusts the mode of drug addition (S73). More specifically, the adjustment unit 107 reduces the drug injection rate. Then, the process returns to step S71. In S73, the adjustment unit 107 may reduce the drug injection rate by directly controlling a supply device that supplies the drug to the flocculator 5, or may reduce the drug injection rate by controlling the supply device via another device such as the control device 3. The same applies to S76 described below.

[0134] In this way, the processes of S71 to S73 are repeated until the determination in S72 is NO. The processes of S71 to S73 are processes for gradually reducing the chemical injection rate by a predetermined reduction amount to a level where a reduction in the predicted value of the water content cannot be expected.

[0135] If the predicted value is increased in step S72 (NO in S72), the adjustment unit 107 performs a process of determining the effect of increasing the drug injection rate (S74).

[0136] 18 is a flow chart showing an example of the drug injection rate increase effect judgment process. First, the prediction unit 102 predicts the water content (S91). More specifically, the prediction unit 102 calculates a first predicted value using first measurement data related to the properties of the liquid after the addition of the drug at the time of performing the process of S91.

[0137] Next, the adjusting unit 107 increases the drug injection rate (S92). The amount of increase in the drug injection rate may be determined in advance. For example, the adjusting unit 107 may increase the drug injection rate by the same amount as in S82 in FIG.

[0138] Next, the prediction unit 102 predicts the water content from the measurement data measured after increasing the drug injection rate in step S92 (S93). More specifically, the prediction unit 102 calculates a second predicted value using second measurement data related to the properties of the liquid after the drug injection rate has been changed by the process of S92. The second measurement data is measured after a sufficient amount of time has passed since the drug injection rate was increased in S92 for the effect of the increase to appear in the measurement data. For example, the second measurement data may be measured when a time (Δt) has passed since the drug injection rate was increased in step S92, similar to S83 in FIG. 17.

[0139] Next, the adjustment unit 107 returns the drug injection rate to the value before it was increased in S92 (S94). Next, the prediction unit 102 predicts the water content from the measurement data measured after the drug injection rate was returned in step S94 (S95). More specifically, the prediction unit 102 calculates a third predicted value using third measurement data related to the properties of the liquid after the drug addition state is returned to the state immediately before step S42 by the process of step S94. Thereafter, the process of FIG. 18 ends, and the process returns to the original process of FIG. 16, and proceeds to step S75.

[0140] In step S75, the adjustment unit 107 determines whether the predicted value of the moisture content has decreased due to the adjustment to increase the drug injection rate based on the first to third predicted values ​​calculated in S74 (S75). If the predicted value of the moisture content has increased or remained unchanged (NO in S75), the process of FIG. 16 ends and returns to the original process.

[0141] On the other hand, if the predicted value of the water content has decreased (YES in S75), the adjusting unit 107 adjusts the mode of drug addition (S76). More specifically, the adjusting unit 107 increases the drug injection rate. Then, the process returns to step S74.

[0142] In this way, the processes of S74 to S76 are repeated until the determination in S75 is NO. The processes of S74 to S76 are processes for gradually increasing the chemical injection rate by a predetermined reduction rate to a level at which a decrease in the predicted value of the water content can no longer be expected.

[0143] Then, the adjustment unit 107 repeats the processes of S71 to S73 until S72 is judged as NO, and then repeats the processes of S74 to S76, thereby adjusting the drug injection rate to a value that is expected to minimize the water content and is not excessive.

[0144] [Embodiment 6] Yet another embodiment of the present invention will be described with reference to Fig. 19 to Fig. 21. A control system 100 according to this embodiment differs from the control system 100 shown in Fig. 2 in the configuration of an information processing device 1, but the other configurations are similar.

[0145] Fig. 19 is a block diagram showing an example of a main configuration of the information processing device 1 of this embodiment. The information processing device 1 of this embodiment is different from the information processing device 1 shown in Fig. 14 in that the name of the instruction unit 103 has been changed to a first instruction unit 103 (a control unit for a dehydrator) and that a second instruction unit 108 (a control unit for an agitating blade) is further provided, but the other configurations are the same.

[0146] The second instruction unit 108 issues instructions regarding the agitator blade 52 to the flocculator control device 3a (agitator blade control unit) via the communication unit 12. In this embodiment, the acquisition unit 101 acquires measurement data on the size of flocs formed in the coagulation tank 51. If the size of the flocs is outside a predetermined appropriate range, the second instruction unit 108 instructs the dehydrator control device 3b (dehydrator control unit) to control the rotation speed of the agitator blade 52 so that the size of the flocs falls within the appropriate range. The second instruction unit 108 operates in parallel with the first instruction unit 103 and the adjustment unit 107.

[0147] Furthermore, in this embodiment, if the size of the flock is outside the sixth predetermined range, first indication unit 103 and adjustment unit 107 stop operating. This makes it possible to prevent the operation of first indication unit 103 and adjustment unit 107 from being adversely affected by the size of the flock being outside the sixth predetermined range. Note that the appropriate range and the sixth predetermined range may be the same or different.

[0148] Fig. 20 is a flowchart showing an example of an instruction process (control method) for the control device 3 in the information processing device 1 having the above configuration. This instruction process is executed periodically (for example, every minute). As shown in Fig. 20, first, the acquisition unit 101 acquires measurement data on the size of flocs formed in the coagulation tank 51 (S101).

[0149] Next, the second instruction unit 108 judges whether the size of the flock is smaller than a predetermined appropriate range, is within the appropriate range, or is larger than the appropriate range (S102). If the size of the flock is within the appropriate range, the second instruction unit 108 ends the instruction process.

[0150] If the size of the flocs is smaller than the appropriate range in step S102, the second instruction unit 108 instructs the flocculator control device 3a to reduce the rotation speed of the mixing blade 52 by a predetermined amount (for example, 1 rotation / min). Then, the instruction process ends. By periodically repeating steps S101 to S103, the size of the flocs can be increased stepwise and finally brought into the appropriate range.

[0151] On the other hand, if the size of the flocs is larger than the appropriate range in step S102, the second instruction unit 108 instructs the flocculator control device 3a to increase the rotation speed of the mixing blade 52 by a predetermined amount (e.g., 1 rotation / min). Then, the instruction process ends. By periodically repeating steps S101, S102, and S104, the size of the flocs can be reduced stepwise and finally brought into the appropriate range.

[0152] Fig. 21 is a flowchart showing an example of the process of the control unit 10 in the information processing device 1 having the above-mentioned configuration. The flowchart shown in Fig. 21 is different from the flowchart shown in Fig. 15 in that step S111 is provided between step S61 and step S62, but the other processes are similar. Note that the process of Fig. 21 is performed in parallel with the process of Fig. 20.

[0153] In step S111, the control unit 10 waits until the size of the flocs formed in the coagulation tank 51 falls within a sixth predetermined range. This makes it possible to stop the operations of the first instruction unit 103 and the adjustment unit 107 when the size of the flocs falls outside the sixth predetermined range.

[0154] (Additional Notes) In the above embodiment, the prediction unit 102 predicts the moisture content of the dehydrated cake at a time point using the machine learning prediction model 111, but the present invention is not limited to this. For example, the prediction unit 102 may predict the moisture content of the dehydrated cake based on a predetermined calculation formula. In addition, in the above embodiment, the information processing device 1 and the control device 3 are separate, but they may be integrated.

[0155] [Software implementation example] The functions of the information processing device 1 (hereinafter referred to as the "device") can be realized by a program for causing a computer to function as the device, and a program for causing a computer to function as each control block of the device (particularly each part included in the control unit 10).

[0156] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program to realize each function described in each of the above embodiments.

[0157] The program may be non-transitory and may be recorded in one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be provided to the device via any wired or wireless transmission medium.

[0158] In addition, some or all of the functions of each of the control blocks can be realized by a logic circuit. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of the present invention. In addition, the functions of each of the control blocks can be realized by, for example, a quantum computer.

[0159] Furthermore, each process described in each of the above embodiments may be executed by AI (Artificial Intelligence). In this case, the AI ​​may be executed by the control device or another device (for example, an edge computer or a cloud server).

[0160] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of symbols]

[0161] 1. Information processing device 3. Control device 3a Flocculator control device (chemical control unit, mixing blade control unit) 3b Dehydrator control device (dehydrator control unit) 5 Flocculator 9 Dehydrator 10 Control section 11 Storage section 51 Coagulation tank 52 Mixing blade 53 Motor 54 Inspection window 55 Sludge inlet 56 Drug inlet 57 Outlet 71 Lighting Equipment 72 Imaging Equipment 91 Outer body screen 92 Screw 93 Sludge inlet 94 Liquid outlet 95 Dehydrated cake outlet 100 Control System 101 Acquisition Department 102 Prediction section, first prediction section 103 Indication unit (control unit), first indication unit (control unit for dehydrator) 104 Second Prediction Section 105 Indication unit (control unit) 106 Update section 107 Adjustment unit (drug control unit) 108 Second indicator (control unit for mixing blade) 111 Predictive Model 112 Estimation Model

Claims

1. an acquisition unit that acquires measurement data including at least a flow rate of the liquid that is supplied to a screw press type dehydrator that transports and dehydrates the liquid discharged from a coagulation tank in which a chemical that coagulates the suspended solids is added to the liquid containing the suspended solids; a first prediction unit that predicts, using the measurement data acquired by the acquisition unit, a moisture content of a dehydrated cake discharged from the dehydrator at a time when a retention time during which the liquid is retained in the dehydrator has elapsed from a time when the measurement data was measured; and a control device comprising: a control unit that, when the flow rate of the liquid acquired by the acquisition unit is outside a first predetermined range, controls the rotation speed of the screw so that the flow rate of the liquid is within the first predetermined range, and, when the flow rate of the liquid is within the first predetermined range and the moisture content of the dehydrated cake predicted by the first prediction unit is outside a second predetermined range, controls the rotation speed of the screw so that the moisture content of the dehydrated cake is within the second predetermined range.

2. A second prediction unit predicts a time to stop the operation of the dehydrator based on the measurement data acquired by the acquisition unit, The control unit is When the flow rate of the liquid is within the first predetermined range and the predicted time predicted by the second prediction unit is outside a third predetermined range, the rotation speed of the screw is controlled so that the predicted time falls within the third predetermined range, and 2. The control device according to claim 1, wherein, when the flow rate of the liquid is within the first predetermined range, the predicted time is within the third predetermined range, and the moisture content of the dehydrated cake is outside the second predetermined range, the rotation speed of the screw is controlled so that the moisture content of the dehydrated cake is within the second predetermined range.

3. an acquisition unit that acquires measurement data including at least a flow rate of the liquid that is supplied to a screw press type dehydrator that transports and dehydrates the liquid discharged from a coagulation tank in which a chemical that coagulates the suspended solids is added to the liquid containing the suspended solids; a first prediction unit that predicts, using the measurement data acquired by the acquisition unit, a moisture content of a dehydrated cake discharged from the dehydrator at a time when a retention time during which the liquid is retained in the dehydrator has elapsed from a time when the measurement data was measured; and A second prediction unit that predicts a time to stop the operation of the dehydrator based on the measurement data acquired by the acquisition unit; a control unit that controls the rotation speed of the screw so that the flow rate of the liquid acquired by the acquisition unit is within a first predetermined range, the moisture content of the dehydrated cake predicted by the first prediction unit is within a second predetermined range, and the predicted time predicted by the second prediction unit is within a third predetermined range.

4. The measurement data acquired by the acquisition unit includes measurement data related to the operation of the dehydrator, The first prediction unit predicts a moisture content of the dehydrated cake using a prediction model, the prediction model is a prediction model trained using the measurement data acquired by the acquisition unit as an explanatory variable and an estimated value by an estimation model for a moisture content of a dehydrated cake discharged from the dehydrator at a time point when the retention time has elapsed since the measurement of the measurement data as a response variable, The control device according to any one of claims 1 to 3, wherein the estimation model is an estimation model trained using measurement data relating to the operation of the dehydrator as an explanatory variable and the moisture content of the dehydrated cake discharged from the dehydrator at the time the measurement data is measured as a target variable.

5. The second prediction unit is Obtaining a first time period from an operation start time when the dehydrator is started to a first time, a measured value of a throughput per unit rotation of a screw of the dehydrator during the first time period, and a measured value of a rotation speed of the screw at the first time; and Obtaining a measurement value of the throughput per unit rotation of the screw during the first period, the measurement value being an average value of the measurement values ​​of the throughput per unit rotation of the screw for a predetermined number of days in the past, and a measurement value of the throughput per unit rotation of the screw during an operation period from the operation start time to an operation stop time at which the operation of the dehydrator is stopped, the measurement value being an average value of the measurement values ​​of the throughput for the predetermined number of days in the past; 4. The control device according to claim 2 or 3, which predicts the operating period from a target value of the throughput to be reached during the operating period, using a measured value of the throughput per unit rotation of the screw during the first period, an average value of the measured values ​​of the throughput per unit rotation of the screw during the first period for the specified number of past days, an average value of the measured values ​​of the throughput per unit rotation of the screw during the operating period for the specified number of past days, and a measured value of the rotational speed of the screw at the first time.

6. The control device according to any one of claims 1 to 3, wherein the control unit issues an alarm when the moisture content of the dehydrated cake predicted by the first prediction unit is outside a fourth specified range including the second specified range.

7. The control device according to claim 2 or 3, wherein the control unit issues an alarm when the predicted time predicted by the second prediction unit is outside a fifth predetermined range including the third predetermined range.

8. The control device according to claim 1 , wherein the control unit controls the rotation speed of the screw by increasing or decreasing the rotation speed of the screw by a predetermined amount and periodically performing this.

9. The control unit includes a dehydrator control unit that controls the rotation speed of the screw, and a chemical control unit that controls the addition of the chemical, The control unit alternately operates the dehydrator control unit and the medicine control unit, A control device as described in any one of claims 1 to 3, wherein the drug control unit adjusts the manner of drug addition based on the moisture content of the dehydrated cake predicted by the first prediction unit from the measurement data acquired by the acquisition unit before the manner of drug addition is changed, and the moisture content of the dehydrated cake predicted by the first prediction unit from the measurement data acquired by the acquisition unit after the manner of drug addition is changed.

10. The control unit further includes an agitation blade control unit that controls the rotation speed of the agitation blade in the coagulation tank, The mixing blade control unit operates in parallel with the dehydrator control unit and the chemical control unit, The acquisition unit further acquires measurement data of the size of flocs formed in the coagulation tank, The control device according to claim 9 , wherein the control unit stops operations of the dehydrator control unit and the chemical control unit when the size of the flocs acquired by the acquisition unit falls outside a sixth predetermined range.

11. A control program for causing a computer to function as the control device according to claim 1, the control program causing a computer to function as the first prediction unit and the control unit.

12. A control program for causing a computer to function as the control device according to claim 3, the control program causing a computer to function as the first prediction section, the second prediction section, and the control section.

13. an acquiring step of acquiring measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which a chemical agent for coagulating the suspended solids is added to the liquid containing the suspended solids and supplied to a screw press type dehydrator which transports and dehydrates the liquid; a first prediction step of predicting, using the measurement data acquired in the acquisition step, a moisture content of a dehydrated cake discharged from the dehydrator at a time when a residence time during which the liquid is retained in the dehydrator has elapsed from the time when the measurement data was measured; and a control step of controlling the rotation speed of the screw so that the flow rate of the liquid is within the first predetermined range when the flow rate of the liquid acquired in the acquisition step is outside a first predetermined range, and controlling the rotation speed of the screw so that the moisture content of the dehydrated cake is within the second predetermined range when the flow rate of the liquid is within the first predetermined range and the moisture content of the dehydrated cake predicted in the first prediction step is outside a second predetermined range.

14. an acquiring step of acquiring measurement data including at least a flow rate of the liquid discharged from a coagulation tank in which a chemical agent for coagulating the suspended solids is added to the liquid containing the suspended solids and supplied to a screw press type dehydrator which transports and dehydrates the liquid; a first prediction step of predicting, using the measurement data acquired in the acquisition step, a moisture content of a dehydrated cake discharged from the dehydrator at a time when a residence time during which the liquid is retained in the dehydrator has elapsed from the time when the measurement data was measured; A second prediction step of predicting a time to stop the operation of the dehydrator based on the measurement data acquired in the acquisition step; and a control step of controlling the rotation speed of the screw so that the flow rate of the liquid acquired in the acquisition step is within a first predetermined range, the moisture content of the dehydrated cake predicted in the first prediction step is within a second predetermined range, and the predicted time predicted in the second prediction step is within a third predetermined range.

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