Control device and its control method, 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 control technology for sludge treatment. [Background Art]

[0002] Sludge treatment performed in wastewater treatment facilities such as sewage treatment plants includes a step of dewatering sludge with a dewatering machine. For efficient sludge treatment, it is important to maintain the flow rate of sludge supplied to the dewatering machine within a predetermined range, and to maintain the moisture content of the dewatered cake obtained by dewatering within a predetermined range. For example, the sludge concentration and dewatering system described in Patent Document 1 controls the rotation speed of the screw shaft of the dewatering machine to stably dewater a constant flow rate of sludge. Further, 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 dewatered cake is equal to or lower than a predetermined value. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2012-030158 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2013-208609 [Summary of the Invention] [Problem to be Solved by the Invention]

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

[0005] Furthermore, if the dewatering properties of the supplied sludge deteriorate, the sludge flow rate decreases, and the moisture content of the dewatered 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 dewatered cake increases further. On the other hand, if the screw rotation speed is decreased to maintain the moisture content of the dewatered cake within a predetermined range, as in Patent Document 2, the sludge flow rate decreases further.

[0006] In other words, if you try to maintain the sludge flow rate within a predetermined range, the moisture content of the dewatered cake will fluctuate significantly. On the other hand, if you try to maintain the moisture content of the dewatered cake within a predetermined range, the sludge flow rate will fluctuate significantly.

[0007] One aspect of the present invention aims to maintain both the flow rate of the liquid supplied to the dewatering machine and the moisture content of the dewatered cake discharged from the dewatering machine within a predetermined range. [Means for solving the problem]

[0008] To solve the above problems, a control device according to one aspect of the present invention includes: an acquisition unit that acquires measurement data including at least the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid while transporting the liquid discharged from a flocculation tank to which a chemical agent for flocculating the suspended solids is added; a first prediction unit that uses the measurement data acquired by the acquisition unit to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data; 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 falls within the first predetermined range if the flow rate of the liquid falls outside the first predetermined range, and controls the rotation speed of the screw so that the moisture content of the dewatered cake falls within the second predetermined range if the flow rate of the liquid falls within the first predetermined range and the moisture content of the dewatered cake predicted by the first prediction unit falls outside the second predetermined range.

[0009] Furthermore, a control device according to another aspect of the present invention includes: an acquisition unit that acquires measurement data including at least the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid while transporting the liquid discharged from a flocculation tank to which a chemical agent for flocculating the suspended solids is added; a first prediction unit that uses the measurement data acquired by the acquisition unit to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data; a second prediction unit that uses the measurement data acquired by the acquisition unit to predict the time to stop the operation of the dewatering machine; and a control unit that controls the rotation speed of the screw such that the flow rate of the liquid acquired by the acquisition unit falls within a first predetermined range, the moisture content of the dewatered cake predicted by the first prediction unit falls within a second predetermined range, and the predicted time predicted by the second prediction unit falls within a third predetermined range.

[0010] Furthermore, 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 the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid while transporting the liquid discharged from a coagulation tank to which an agent for coagulating the suspended solids is added; a first prediction step of using the measurement data acquired in the acquisition step to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data; 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 falls within the first predetermined range, while controlling the rotation speed of the screw so that the moisture content of the dewatered cake falls within the second predetermined range, if the flow rate of the liquid is within the first predetermined range and the moisture content of the dewatered cake predicted in the first prediction step falls outside the second predetermined range.

[0011] Furthermore, 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 the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid while transporting the liquid discharged from a coagulation tank to which a chemical agent for coagulating the suspended solids is added; a first prediction step of using the measurement data acquired in the acquisition step to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data; a second prediction step of predicting the time to stop the operation of the dewatering machine based on the measurement data acquired in the acquisition step; and a control step of controlling the rotation speed of the screw such that the flow rate of the liquid acquired in the acquisition step falls within a first predetermined range, the moisture content of the dewatered cake predicted in the first prediction step falls within a second predetermined range, and the predicted time predicted in the second prediction step falls within a third predetermined range. [Effects of the Invention]

[0012] According to one aspect of the present invention, both the flow rate of the liquid supplied to the dewatering machine and the moisture content of the dewatered cake discharged from the dewatering machine can be maintained within a predetermined range. [Brief explanation of the drawing]

[0013] [Figure 1] This is a block diagram showing an example of the main components of an information processing device in a control system according to one embodiment of the present invention. [Figure 2] This figure shows an example of the configuration of the control system described above. [Figure 3] This flowchart shows an example of the instruction processing to the control device in the above-mentioned information processing device. [Figure 4] This graph shows the time evolution of various measured values ​​in one embodiment of the above-described information processing device. [Figure 5] This is a block diagram showing an example of the main components of an information processing device in a control system according to another embodiment of the present invention. [Figure 6]It is a flowchart showing an example of instruction processing for a control device in the above information processing apparatus. [Figure 7] It is a graph showing temporal changes of various measured values in one embodiment of the above information processing apparatus. [Figure 8] It is a block diagram showing an example of the main configuration of an information processing apparatus in a control system according to still another embodiment of the present invention. [Figure 9] It is a graph showing the variation in the estimated moisture content value obtained by the estimation model in the above information processing apparatus with respect to the actually measured moisture content value by an operator. [Figure 10] It is a model diagram showing the concept of creating training data for a prediction model in the above information processing apparatus. [Figure 11] It is a flowchart showing an example of update processing of a prediction model and an estimation model in the above information processing apparatus. [Figure 12] It is a flowchart showing an example of instruction processing for a control device in a control system according to still another embodiment of the present invention. [Figure 13] It is a flowchart showing an example of instruction processing for a control device in the above control system. [Figure 14] It is a block diagram showing an example of the main configuration of an information processing apparatus in a control system according to still another embodiment of the present invention. [Figure 15] It is a flowchart showing an example of processing by a control unit in the above information processing apparatus. [Figure 16] It is a flowchart showing an example of chemical agent ratio adjustment processing in the processing of the above control unit. [Figure 17] It is a flowchart showing an example of chemical dosing rate reduction effect determination processing in the above chemical agent ratio adjustment processing. [Figure 18] It is a flowchart showing an example of chemical dosing rate increase effect determination processing in the above chemical agent ratio adjustment processing. [Figure 19] It is a block diagram showing an example of the main configuration of an information processing apparatus in a control system according to still another embodiment of the present invention. [Figure 20]This flowchart shows an example of the instruction processing to the control device in the above-mentioned information processing device. [Figure 21] This flowchart shows an example of the processing performed by the control unit in the above-mentioned information processing device. [Modes for carrying out the invention]

[0014] The embodiments of the present invention will be described in detail below. For the sake of convenience, components having the same function as those shown in each embodiment will be denoted by the same reference numerals, and their descriptions will be omitted as appropriate.

[0015] [Embodiment 1] One embodiment of the present invention will be described with reference to Figures 1 to 3.

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

[0017] As will be explained in detail below, the control system 100 performs each step of the sludge treatment process, from the step of agglomerating the suspended solids in the sludge to be treated to form flocs, thereby converting the sludge to be treated into agglomerated sludge, to the step of dewatering the agglomerated sludge to obtain dewatered sludge (also called dewatered cake) and dewatered filtrate. As shown in Figure 2, the control system 100 includes an information processing device 1, a control device 3, a flocculator 5, and a dewatering machine 9.

[0018] The flocculator 5 is a device that forms flocs by adding a flocculating agent to the liquid to be treated in the flocculation tank and stirring it appropriately. Specifically, the flocculator 5 uses sludge as the liquid to be treated, flocculates the suspended solids in the sludge to form flocs, and produces flocculated sludge. The flocculator 5 in Figure 2 is equipped with a flocculation tank 51, a stirring blade 52, a motor 53, and an inspection window 54. The flocculator 5 is also provided with a sludge inlet 55, a chemical inlet 56, and a discharge port 57.

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

[0020] The dewatering machine 9 is a device that separates the solids and liquids of the treated liquid in which flocs have formed. Specifically, the dewatering machine 9 is installed downstream of the flocculator 5 and dewaters the flocculated sludge (liquid) discharged from the flocculator 5 to separate the solids and liquids. The dewatering machine 9 in Figure 2 is a screw press type dewatering machine equipped with an outer shell screen 91 and a screw 92. The dewatering machine 9 is also provided with a sludge inlet 93, a filtrate outlet 94, and a dewatered cake outlet 95. Although not shown in the figure, the dewatering machine 9 is also equipped with a motor to rotate the screw 92. Of course, the dewatering machine 9 can be any machine capable of dewatering flocculated sludge and is not limited to a screw press type. For example, a centrifugal dewatering machine, a filter press type dewatering machine, or a belt press dewatering machine can also be used.

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

[0022] Then, a chemical agent (at least containing a coagulant) is introduced into the sludge in the coagulation tank 51 through the chemical inlet 56 to coagulate the sludge. In this state, the motor 53 is driven to rotate the stirring blade 52, stirring the sludge and chemical agent to form flocs. The coagulated sludge, which is a mixture of the formed flocs and the water contained in the sludge, is discharged from the discharge port 57.

[0023] Next, the coagulated sludge is supplied into the outer shell screen 91 from the sludge inlet 93 of the dewatering machine 9. Inside the dewatering machine 9, the coagulated sludge is transported by the screw 92 and dewatered under pressure from the screw 92, the filtrate is discharged from the filtrate outlet 94, and the dewatered cake, which is a mass of dewatered coagulated sludge, is discharged from the dewatered cake outlet 95.

[0024] The sludge is supplied to the coagulation tank 51 from the sludge inlet 55, and the coagulated sludge is pushed out from the discharge port 57 of the coagulation tank 51 and discharged, and the discharged coagulated sludge is supplied to the dewatering machine 9. For this reason, the flow rate of sludge supplied to the coagulation tank 51 and the flow rate of sludge supplied to the dewatering machine 9 coincide at the same time.

[0025] As will be explained in detail below, the information processing device 1 acquires at least one of the following: measurement data regarding the liquid supplied to the coagulation tank 51, measurement data regarding the chemical supplied to the coagulation tank 51, measurement data regarding the liquid inside the coagulation tank 51, measurement data regarding the operation of the coagulation tank 51, and measurement data regarding the operation of the dewatering machine 9. Based on the acquired measurement data, the information processing device 1 predicts the moisture content of the dewatered cake.

[0026] Furthermore, the information processing device 1 can also control the operation of various devices that are components of the control system 100 (for example, the flocculator 5, the dewatering machine 9, and a sludge and chemical supply device not shown) 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 in Figure 2, the control device 3 includes a flocculator control device 3a that controls the equipment related to the flocculator 5, and a dewatering machine control device 3b that controls the equipment related to the dewatering machine 9.

[0027] [Information Processing Device] Figure 1 is a block diagram showing an example of the main components of the information processing device 1. As shown in the figure, the information processing device 1 includes a control unit 10 that controls all parts 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 for the information processing device 1 to communicate with other devices, an input unit 13 that receives input of various data to the information processing device 1, and an output unit 14 for the information processing device 1 to output various data.

[0028] Furthermore, 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 explained later in the section "About the Instruction Unit".

[0029] The memory unit 11 contains a prediction model 111. Details of the prediction model 111 will be explained later in the section "About the Prediction Model".

[0030] The acquisition unit 101 acquires measurement data indicating the flow rate of flocculated sludge supplied to the dewatering machine 9. In addition, the acquisition unit 101 acquires at least one of the following: measurement data related to the liquid supplied to the flocculation tank 51, measurement data related to the chemicals supplied to the flocculation tank 51, measurement data related to the liquid inside the flocculation tank 51, measurement data related to the operation of the flocculation tank 51, and measurement data related to the operation of the dewatering machine 9. Details of each measurement data will be explained later in the section "About the Prediction Model".

[0031] The prediction unit 102 uses the prediction model 111 stored in the storage unit 11 to predict the moisture content of the dewatered cake from the measurement data acquired by the acquisition unit 101. This dewatered cake is the cake discharged from the dewatering machine 9 at the point when the retention time for the coagulated sludge has elapsed in the dewatering machine 9 from the time of measurement of the above measurement data (hereinafter referred to as the "elapsed time"). The prediction unit 102 performs a prediction using the prediction model 111 each time the acquisition unit 101 acquires new measurement data. As a result, the prediction unit 102 can predict the moisture content of the dewatered 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, if the flow rate of the coagulated sludge acquired by the acquisition unit 101 is outside the first predetermined range, the instruction unit 103 instructs the dewatering machine control device 3b to control the rotation speed of the screw 92 so that the flow rate of the coagulated sludge falls within the first predetermined range. Therefore, the first predetermined range corresponds to a predetermined range in which the flow rate of the coagulated sludge is appropriate.

[0033] The upper limit of the first predetermined range described above may be, for example, the upper limit of the flow rate of the pump that supplies the coagulated sludge to the dewatering machine 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 indicator unit 103 can stabilize the flow rate of the coagulated sludge. Furthermore, by further narrowing the first predetermined range, the indicator unit 103 can cause the dewatering machine control device 3b to control the flow rate of the coagulated sludge to remain constant.

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

[0035] [About the predictive model] The prediction model 111 uses the measurement data acquired by the acquisition unit 101 at the time of measurement as the explanatory variable, and the moisture content of the dewatered cake discharged from the dewaterer 9 at the time of elapsed time (hereinafter referred to as "moisture content at the time of elapsed time") as the dependent variable, and models the relationship between these two variables. For example, a prediction model generated by machine learning using training data that shows the correspondence between previously measured measurement data and the moisture content corresponding to that measurement data can also be used. The algorithm of the prediction model 111 is not particularly limited, and prediction models such as regression or multiple regression models, neural networks, or random forests can also 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 relating to the sludge supplied to the coagulation tank 51. This measurement data includes, for example, the supply flow rate of the sludge per unit time and at least one of the sludge concentration, and is measured before the sludge inlet 55.

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

[0039] (3) Measurement data relating to the sludge in the coagulation tank 51. This measurement data consists of at least one of the average density 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 imaging device 72. The average density value serves as an indicator of the sludge color (brightness / darkness). The average unit area serves as an indicator of the floc diameter.

[0040] (4) Measurement data relating to the operation of the flocculation tank 51. This measurement data is the rotational speed of the stirring blade 52 in the flocculation tank 51 and is obtained from the flocculator control device 3a.

[0041] (5) Measurement data relating to the operation of the dewatering machine 9. This measurement data includes at least one of the following: the operating time of the dewatering machine 9, the rotational speed of the screw 92 of the dewatering machine 9, the flow rate of flocculated sludge supplied to the dewatering machine 9 per unit time, and the input pressure of the flocculated sludge fed into the dewatering machine 9, and is obtained from the dewatering machine control device 3b.

[0042] In this embodiment, various measurement data can be used as shown in (1) to (5) above. Therefore, the moisture content of the dewatered cake can be predicted with high accuracy using multifaceted explanatory variables. Among the measurement data shown in (1) to (5) above, the measurement data that contributes most to the prediction accuracy of the prediction model 111 are the operating time, the rotational speed of the screw 92, and the supply flow rate shown in (5) above, and the average density value of the flocs shown in (3) above.

[0043] According to the above configuration, the control unit 10 first controls the rotation speed of the screw 92 so that the flow rate of the flocculated sludge supplied to the dewatering machine 9 falls within the first predetermined range if the flow rate of the flocculated sludge falls outside 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, the rotational speed of the screw 92 is changed, which may cause the moisture content of the dewatered cake to fall outside the second predetermined range. However, the point at which the moisture content of the dewatered cake actually falls outside the second predetermined range is when the residence time has elapsed since the measurement of the flow rate of the flocculated sludge.

[0045] Therefore, when the prediction unit 102 predicts the moisture content of the dewatered cake for the next time, if the flow rate of the flocculated sludge is within the first predetermined range and the moisture content of the dewatered 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 dewatered cake falls within the second predetermined range. As a result, the moisture content of the dewatered cake can be maintained within the second predetermined range after the residence time has elapsed from the time the flow rate of the flocculated sludge is measured.

[0046] [Instruction Processing] Figure 3 is a flowchart showing an example of the instruction processing (control method) to the control device 3 in the information processing device 1 with the above configuration. This instruction processing is performed periodically (for example, every 5 minutes). As shown in Figure 3, first, the acquisition unit 101 collects (acquires) various measurement data (S11). Next, the prediction unit 102 uses the prediction model 111 to predict the moisture content of the dewatered cake discharged from the dewatering machine 9 at a point in time after the residence time has elapsed from the measurement time of the measurement data (S12).

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

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

[0049] On the other hand, if the flow rate of the flocculated sludge in step 13 is within the first predetermined range, the indicator unit 103 determines whether the predicted value of the moisture content of the dewatered cake at the above time point, as predicted in step S12, is smaller than the second predetermined range, within the second predetermined range, or larger than the second predetermined range (S14).

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

[0051] In step S15, the instruction unit 103 instructs the dewatering machine control device 3b to increase the rotational speed of the screw 92 of the dewatering machine 9 by a predetermined amount (for example, 0.01 revolutions / minute). After that, the instruction process is terminated. By periodically repeating steps S11 to S13 and S15, the flow rate of the flocculated sludge increases in stages and can eventually be brought within the first predetermined range. Furthermore, by periodically repeating steps S11 to S14 and S15, the predicted value of the moisture content of the dewatered cake at the above time points increases in stages and can eventually be brought within the second predetermined range.

[0052] In step S16, the instruction unit 103 instructs the dewatering machine control device 3b to reduce the rotational speed of the screw 92 of the dewatering machine 9 by a predetermined amount. After that, the instruction process is terminated. By periodically repeating steps S11 to S13 and S16, the flow rate of the flocculated sludge is gradually reduced and can finally be brought within the first predetermined range. Furthermore, by periodically repeating steps S11 to S14 and S16, the predicted value of the moisture content of the dewatered cake at the above time points is gradually reduced and can finally be brought within the second predetermined range.

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

[0054] [Additional Notes] In the above-described embodiment, the prediction unit 102 predicts the moisture content of the dehydrated cake from the measurement data using the learned prediction model 111, but it 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] [Examples] Figure 4 is a graph showing the time variation of various measured values ​​in one embodiment of the information processing device 1 configured as described above. The horizontal axis of Figure 4 represents the operating time (minutes). The vertical axis of Figure 4 represents the measured values ​​of each measurement data, shown on an arbitrary scale for each measurement data. The measured values ​​in Figure 4 are the dewatering properties of the supplied flocculated sludge, the flow rate of the flocculated sludge, the water content of the dewatered cake, and the rotation speed of the screw 92.

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

[0057] In Figure 4, when the dewatering properties of the coagulated sludge decrease, the water content of the dewatered cake increases after the retention time has elapsed. Therefore, in the comparative example, the rotation speed of screw 92 is gradually reduced. However, in this case, the flow rate of the coagulated sludge decreases significantly.

[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 flocculated sludge remains within a first predetermined range. This prevents a significant decrease in the flow rate of the flocculated sludge. Furthermore, in this embodiment, once the flow rate of the flocculated sludge is 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 dewatered cake remains within a second predetermined range. This prevents a significant increase in the moisture content of the dewatered cake.

[0059] Furthermore, as shown in Figure 4, an increase in the dewatering properties of the flocculated sludge leads to a decrease in the water content of the dewatered cake after the retention period has elapsed. Therefore, in the comparative example, the rotation speed of the screw 92 is increased in stages. 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 remains within a first predetermined range. This prevents a significant decrease in the flow rate of the flocculated sludge. Furthermore, in this embodiment, once the flow rate of the flocculated sludge is within the first predetermined range, the increase in the rotational speed of the screw 92 is maintained so that the moisture content of the dewatered cake remains within a second predetermined range. This prevents a significant decrease in the moisture content of the dewatered cake.

[0061] [Embodiment 2] Another embodiment of the present invention will be described with reference to Figures 5 and 6. The control system 100 according to this embodiment differs from the control system 100 shown in Figure 2 in the configuration of the information processing device 1, but the other configurations are the same.

[0062] Figure 5 is a block diagram showing an example of the main components 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 Figure 1 in that the prediction unit 102 is renamed to the first prediction unit 102, the control unit 10 further includes a second prediction unit 104, and the instruction unit 103 is replaced with an instruction unit 105 (control unit). The other components are the same.

[0063] Incidentally, for efficient sludge treatment, it is desirable to predict when to end the operation of the dewatering machine 9, based on the total processing volume in the dewatering machine 9, such as the flow rate of the flocculated sludge and the weight of the dewatered cake, reaching the daily target value. In this case, the operator can carry out the processing without delay after the dewatering machine 9 has finished operating.

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

[0065] Specifically, the second prediction unit 104 first obtains a target value DAt for the processing volume of the dewatering machine 9. The second prediction unit 104 also obtains a first period T1 from the start time t0 when the dewatering machine 9 starts operating to a first time t1, a measured value A1 for the processing volume per unit rotation of the screw 92 during the first period T1, and a measured value rr1 for the rotational speed of the screw 92 at the first time t1. The processing volume may be, for example, the amount of flocculated sludge supplied to the dewatering machine 9, or the amount of dewatered cake discharged from the dewatering machine 9.

[0066] Next, the second prediction unit 104 obtains PA1, which is the average value of the measured processing amount per unit rotation of the screw 92 over a predetermined number of past days, and is a measured value A1 of the processing amount per unit rotation of the screw 92 during the first period T1. The second prediction unit 104 also obtains PA2, which is the average value of the measured processing amount per unit rotation of the screw 92 over the predetermined number of past days, and is a measured value of the processing amount per unit rotation of the screw 92 during the operating period Top from the start time t0 to the stop time te.

[0067] Next, the second prediction unit 104 uses the measured value A1 of the processing amount per unit rotation of the screw 92 during the first period T1, the average value PA1 of the measured values ​​of the processing amount per unit rotation of the screw 92 during the first period T1 over the predetermined number of past days, the average value PA2 of the measured values ​​of the processing amount per unit rotation of the screw 92 during the operating period Top over the predetermined number of past days, and the measured value rr1 of the rotational speed of the screw 92 at the first time t1 to predict the operating period Top from the target value DAt of the processing amount that should be reached, based on the following equation (1). DAt / Top=A1×(PA2 / PA1)×rr1 ····(1). The second prediction unit 104 then outputs a predicted value for the shutdown time te, which is obtained by adding the start time t0 to the predicted value for the operating period Top. The second prediction unit 104 may also predict the shutdown 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 Figure 1, if the flow rate of the coagulated sludge acquired by the acquisition unit 101 falls outside a first predetermined range, the instruction unit 105 instructs the dewatering machine control device 3b to control the rotation speed of the screw 92 so that the flow rate of the coagulated sludge falls within the first predetermined range. Therefore, the first predetermined range corresponds to a predetermined range in which the flow rate of the coagulated sludge is appropriate.

[0069] Furthermore, if the flow rate of the flocculated sludge is within the first predetermined range, and the predicted time for stopping operation predicted by the second prediction unit 104 is outside the third predetermined range, the instruction unit 105 instructs the dewatering machine 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 for stopping operation is appropriate.

[0070] Furthermore, if the flow rate of the flocculated sludge is within a first predetermined range, the predicted time for stopping the operation is within a third predetermined range, and the predicted value of the moisture content of the dewatered cake predicted by the first prediction unit 102 is outside the second predetermined range, the instruction unit 103 instructs the dewatering machine control device 3b to control the rotation speed of the screw 92 so that the predicted value of the moisture content of the dewatered cake falls within the second predetermined range. Therefore, the second predetermined range corresponds to a predetermined range in which the moisture content of the dewatered cake is appropriate.

[0071] Incidentally, if the flow rate of the flocculated sludge is within the first predetermined range and the moisture content of the dewatered 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 dewatered cake falls within the second predetermined range. At this time, the change in the rotation speed of the screw 92 may cause the flow rate of the flocculated sludge to change within the first predetermined range, potentially changing the time at which the amount of flocculated sludge or the dewatered cake reaches the target value. As a result, the time at which the operation of the dewatering machine 9 is stopped may change.

[0072] Therefore, in this embodiment, the control unit 10 predicts the time to stop the operation of the dewatering machine 9 based on the measurement data, and if the predicted time for stopping the operation falls outside the third predetermined range, it controls the rotation speed of the screw 92 so that the predicted time falls within the third predetermined range. Furthermore, if the flow rate of the flocculated sludge is within the first predetermined range, the predicted time falls within the third predetermined range, and the moisture content of the dewatered cake falls outside the second predetermined range, the control unit 10 controls the rotation speed of the screw 92 so that the moisture content of the dewatered cake falls within the second predetermined range. As a result, although there is a possibility that the moisture content of the dewatered cake will change significantly, the predicted time for stopping the operation can be maintained within the third predetermined range. As a result, the operation of the dewatering machine 9 can be stopped as scheduled, and post-operation processing such as transporting the dewatered cake can be carried out as scheduled.

[0073] Figure 6 is a flowchart showing an example of the instruction processing (control method) for the control device 3 in the information processing device 1 with the above configuration. The instruction processing in this embodiment differs from the instruction processing shown in Figure 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 processing is the same.

[0074] In step S21, the second prediction unit 104 predicts the time when the dewatering machine 9 will stop operating based on the measurement data. Note that steps S12 and S21 may be processed first or simultaneously.

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

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

[0077] Therefore, if the predicted value in step S14 is within the second predetermined range, 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 terminates the instruction process. Furthermore, by periodically repeating steps S11, S12, S21, S13, S22, and S15, the predicted time for stopping the operation can be gradually increased until it falls within the third predetermined range. Furthermore, by periodically repeating steps S11, S12, S21, S13, S22, and S16, the predicted time for stopping the operation can be gradually decreased until it falls within the third predetermined range.

[0078] [Examples] Figure 7 is a graph showing the time variation of various measured values ​​in one embodiment of the information processing device 1 configured as described above. The horizontal axis of Figure 7 represents the operating time (minutes). The vertical axis of Figure 7 represents the measured values ​​of each measurement data, which are shown on an arbitrary scale for each measurement data. The measured values ​​in Figure 7 are the dewatering properties of the supplied flocculated sludge, the deviation in the operation stop time, the flow rate of the flocculated sludge, the water content of the dewatered cake, and the rotation speed of the screw 92.

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

[0080] In Figure 7, when the dewatering properties of the flocculated sludge decrease, the water content of the dewatered cake increases after the retention period. Therefore, in the comparative example, the rotation speed of screw 92 is gradually reduced. However, in this case, the expected time of shutdown becomes significantly delayed, and the flow rate of the flocculated sludge decreases greatly.

[0081] In contrast, in this embodiment, the amount of decrease 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 prevents a significant decrease in the flow rate of the flocculated sludge. Furthermore, in this embodiment, when the flow rate of the flocculated sludge falls within the first predetermined range, the rotational speed of the screw 92 is increased so that the predicted time of shutdown falls within a third predetermined range. This prevents the predicted time of shutdown from being significantly delayed.

[0082] In this embodiment, when the flow rate of the flocculated sludge falls within a first predetermined range and the predicted time for stopping operation falls within a third predetermined range, the reduction in the rotational speed of the screw 92 is maintained so that the moisture content of the dewatered cake falls within a second predetermined range. This prevents a significant increase in the moisture content of the dewatered cake.

[0083] Furthermore, as shown in Figure 7, an increase in the dewatering properties of the flocculated sludge leads to a decrease in the water content of the dewatered cake after the retention period has elapsed. Therefore, in the comparative example, the rotation speed of the screw 92 is increased in stages. However, in this case, the expected time of shutdown becomes significantly earlier, and the flow rate of the flocculated sludge increases greatly.

[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 flocculated sludge falls within a first predetermined range. This prevents a large increase in the flow rate of the flocculated sludge. Furthermore, in this embodiment, when the flow rate of the flocculated sludge falls within the first predetermined range, the rotational speed of the screw 92 is reduced so that the predicted time of shutdown falls within a third predetermined range. This prevents the predicted time of shutdown from becoming significantly earlier.

[0085] In this embodiment, when the flow rate of the flocculated sludge falls within a first predetermined range and the predicted time for stopping the operation falls within a third predetermined range, the increase in the rotational speed of the screw 92 is maintained so that the moisture content of the dewatered cake falls within a second predetermined range. This prevents a significant decrease in the moisture content of the dewatered cake.

[0086] [Additional Notes] Steps S13, S22, and S14 may be processed in any order. That is, the instruction unit 105 may instruct the dewatering machine 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 falls within a first predetermined range, the predicted value of the moisture content of the dewatered cake predicted by the first prediction unit 102 falls within a second predetermined range, and the predicted time for stopping operation predicted by the second prediction unit 104 falls within a third predetermined range.

[0087] In this case, the dewatering machine 9 can be operated while maintaining the flow rate of the coagulated sludge and the moisture content of the dewatered cake within an appropriate range, the dewatering machine 9 can be stopped as scheduled, and post-stop processing, such as transporting the dewatered cake, can be carried out as scheduled.

[0088] [Embodiment 3] Further embodiments of the present invention will be described with reference to Figures 8 to 11. The control system 100 according to this embodiment differs from the control system 100 shown in Figure 2 in the configuration of the information processing device 1, but the other configurations are the same.

[0089] Figure 8 is a block diagram showing an example of the main components 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 Figure 1 in that the storage unit 11 further includes an estimated model 112 and an update unit 106 is further provided, but the other components are the same.

[0090] [Regarding the estimation model] In this embodiment, the moisture content at elapsed time points, which is the objective variable of the prediction model 111, is an estimated value obtained by the estimation model 112. The estimation model 112 is an estimation model that has been learned with measurement data related to the operation of the dewatering machine 9 from the measurement data acquired by the acquisition unit 101 as the explanatory variable, and the moisture content of the dewatered cake discharged from the dewatered cake discharge port 95 of the dewatering machine 9 (hereinafter referred to as "moisture content at the time of measurement") at the time of measurement of said measurement data as the objective variable.

[0091] The above measurement data includes at least one of the following: the operating time of the dewatering machine 9, the rotational speed of the screw of the dewatering machine 9, the drive current value or torque value of the screw, the back pressure from the back pressure plate that compresses the liquid and is provided at the dewatering cake discharge port 95 (discharge section) of the dewatering machine 9, and the opening degree between the back pressure plate and the dewatering cake discharge port 95. These are obtained from the dewatering machine control device 3b. Of these, the measurement data that contribute most significantly to the estimation accuracy of the estimation model 112 are the drive current value of the screw and the opening degree (especially when the dewatering machine 9 is controlled so that the back pressure remains constant). The moisture content is measured manually by an operator using an external device to the control system 100. For this reason, this measurement cannot be performed frequently.

[0092] Figure 9 is a graph showing the variation in moisture content estimates from the estimation model 112 compared to actual moisture content measurements by the operator. In the example in Figure 9, the explanatory variables are the operating time of the dewatering machine 9, the rotational speed and drive current value of the screw of the dewatering machine 9, the back pressure from the back pressure plate, and the opening degree between the back pressure plate and the dewatered cake discharge port 95. Referring to Figure 9, it can be seen that the above variation is extremely small. Therefore, by using measurement data related to the operation of the dewatering machine 9 with the estimation model 112, the moisture content at the time of measurement can be estimated accurately and frequently. As a result, the moisture content of the dewatered cake can be predicted accurately without increasing the workload on the operator in the manual analysis of the moisture content of the dewatered cake.

[0093] [Methods for training predictive models] Next, the method for learning moisture content using the prediction model 111 of this embodiment will be described. As described above, the prediction model 111 is a model that uses measurement data at the time of measurement to predict the moisture content at a future time point beyond the measurement time.

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

[0095] The explanatory variables for the prediction model 111, as shown in the upper part of Figure 10, are the supply flow rate of liquid (sludge) per unit time, the concentration of liquid (sludge), the average density of flocs, the average unit area of ​​gaps between flocs, the rotation speed of the agitator blades in the coagulation tank 51, the operating time of the dewatering machine 9, the rotation speed of the screw of the dewatering machine 9, and the input pressure of the liquid (coagulated sludge) fed into the dewatering machine 9.

[0096] The dependent variable in the prediction model 111 is the moisture content at each point in time. If actual measurements taken by workers are used as this moisture content, there is a limit to the number of measurements a worker can take in a day, as shown by the white circles in the lower part of Figure 10. Therefore, the number of training data, which are combinations of explanatory and dependent variables, is limited, making it difficult to create a highly accurate prediction model.

[0097] Therefore, in this embodiment, instead of using actual measurements by workers as the target variable for the training data, the estimated values ​​from the estimation model 112 described above are used. As a result, as shown by the gray circles in the lower part of Figure 10, the number of target variables is no longer limited by the number of measurements that workers can take, so the amount of training data can be increased, and a highly accurate prediction model 111 can be created.

[0098] Incidentally, the estimated moisture content at the above-mentioned time points is calculated using estimation model 112 from the measurement data at those time points. Therefore, the training of prediction model 111 utilizes the measurement data at the measurement points, which are explanatory variables of prediction model 111, and the measurement data at the time points, which are explanatory variables of estimation model 112.

[0099] [Method for predicting moisture content using a predictive model] The prediction unit 102 uses the trained prediction model 111 to predict the moisture content of the dewatered cake. Specifically, the prediction unit 102 inputs at least one of the explanatory variables—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 inside the coagulation tank 51, measurement data on the operation of the coagulation tank 51, and measurement data on the operation of the dewatering machine 9—into the prediction model 111 to predict the objective variable, which is the moisture content of the dewatered cake at the completion of dewatering.

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

[0101] [Regarding the update section] The update unit 106 performs the process of updating the prediction model 111 and the estimation model 112 during the period when the coagulation tank 51 and the dewatering machine 9 are stopped (downtime). Specifically, the update unit 106 updates the estimation model 112 during the downtime using the pair of measurement data acquired by the acquisition unit 101 during the operation period of the dewatering machine 9 and the moisture content of the dewatered cake measured by the operator as training data.

[0102] Next, the update unit 106 updates the prediction model during the shutdown period using as training data a pair of measurement data acquired by the acquisition unit 101 during the operation period of the coagulation tank 51 and the dewatering machine 9, and an estimated value from the estimation model 112 regarding the moisture content of the dewatered cake discharged from the dewatering machine 9 at a point in time after the residence time has elapsed from the measurement point of the measurement data.

[0103] Typically, the above operating period is one set period within a day. Therefore, the update by the update unit 106 is performed once a day. Also, the actual measurement of the moisture content of the dewatered cake by the operator takes about a day. For this reason, the update of the estimation model 112 may use measurement data from the above operating period two days prior, for example. On the other hand, it is desirable to use measurement data from the most recent operating period when updating the prediction model 111.

[0104] Therefore, since the prediction model 111 is updated using the latest measurement data, the predictions using the prediction model 111 can be adapted to the latest conditions of the coagulation tank 51 and the dewatering machine 9. Similarly, since the estimation model 112 is updated using the latest measurement data and the operator's actual measurements, the estimations using the estimation model 112 can be adapted to the latest conditions of the dewatering machine 9.

[0105] [Update process] Figure 11 is a flowchart showing an example of the update process for the prediction model 111 and estimation model 112 in the information processing device 1. This update process is performed after each downtime, as described above.

[0106] As shown in Figure 11, first, the acquisition unit 101 determines whether or not a new measured value of moisture content has been acquired by the worker (S31). If the above measured value has not been acquired (NO in S31), the process proceeds to step S34. On the other hand, if the above measured value has been acquired (YES in S31), the update unit 106 creates a new training data set consisting of the newly acquired measured value of moisture content and the measurement data at the time of the measurement (S32), and updates the estimation model 112 using the created training data (S33).

[0107] Next, the update unit 106 uses the estimation model 112 to calculate an estimated value of the moisture content during the most recent operating period from the measurement data of that operating period (S34). Next, for each measurement point in the most recent operating period, the update unit 106 creates a new training data set consisting of the measurement data at that point and the estimated value at a later point in time after the residence time has elapsed since that measurement point (S35). Then, the update unit 106 updates the prediction model 111 using the created training data (S36). After that, the update process is terminated.

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

[0109] [Embodiment 4] Another embodiment of the present invention will be described with reference to Figures 12 and 13. The control system 100 according to this embodiment differs from the control system 100 shown in Figure 2 in that it has an additional operation to instruct the instruction unit 105 of the information processing device 1 shown in Figure 5 to issue an alarm, but the other configurations are the same.

[0110] Specifically, the instruction unit 105 instructs the output unit 14 to issue an alarm if the flow rate of the coagulated sludge falls outside the first predetermined range and the predicted moisture content of the dewatered cake falls outside the fourth predetermined range which includes the second predetermined range. The instruction unit 105 also instructs the output unit 14 to issue an alarm if the predicted time predicted by the second prediction unit 104 falls outside the fifth predetermined range which includes the third predetermined range. This allows for alerting the operator.

[0111] Figures 12 and 13 are flowcharts showing an example of instruction processing (control method) to the control device 3 in the information processing device 1 with the above configuration. The instruction processing in this embodiment differs from the instruction processing shown in Figure 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 processing is the same.

[0112] As shown in Figure 12, in step S13, if the flow rate of the flocculated sludge is less than the first predetermined range, the instruction unit 105 instructs the dewatering machine control device 3b to increase the rotation speed of the screw 92 of the dewatering machine 9 by a predetermined amount, similar to step S15 (S41). Next, if the predicted value of the moisture content of the dewatered cake is greater than the fourth predetermined range which includes the second predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm, indicating that the predicted value is too high (S42). Also, if the predicted time for stopping the operation is earlier than the fifth predetermined range which includes the third predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm, indicating that the predicted time is too early (S42). After that, the instruction process is terminated.

[0113] On the other hand, if the flow rate of the flocculated sludge in step S13 is greater than the first predetermined range, the instruction unit 105 instructs the dewatering machine control device 3b to reduce the rotation speed of the screw 92 of the dewatering machine 9 by a predetermined amount, similar to step S16 (S43). Next, if the predicted value of the moisture content of the dewatered cake is smaller than the fourth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm, indicating that the predicted value is too small (S44). Also, if the predicted time for stopping the operation is later than the fifth predetermined range, the instruction unit 105 instructs the output unit 14 to issue an alarm, indicating that the predicted time is too late (S44). After that, the instruction processing is terminated.

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

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

[0116] Furthermore, as shown in Figure 13, if the predicted value in step S14 is smaller than the second predetermined range, the instruction unit 105 instructs the dewatering machine control device 3b to increase the rotational speed of the screw 92 of the dewatering machine 9 by a predetermined amount, similar to step S15 (S49). After that, the instruction process is terminated.

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

[0118] [Embodiment 5] Further embodiments of the present invention will be described with reference to Figures 14 to 18. The control system 100 according to this embodiment differs from the control system 100 shown in Figure 2 in the configuration of the information processing device 1, but the other configurations are the same.

[0119] Figure 14 is a block diagram showing an example of the main components 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 Figure 1 in that it is further provided with an adjustment unit 107 (pharmaceutical control unit), but the other components are the same.

[0120] The adjustment unit 107 adjusts the method of adding the drug 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 drug has been added, and a second predicted value predicted by the prediction unit 102 using second measurement data related to the properties of the liquid after the method of adding the drug has been changed. The adjustment unit 107 instructs the flocculator control device 3a (drug control unit) to add the drug according to the adjusted method. This makes it possible to appropriately adjust the method of adding the drug that causes suspended solids to flocce when added to a liquid containing suspended solids.

[0121] [Methods for adjusting the manner in which drugs are added] The adjustment unit 107 adjusts the method of drug addition based on the first and second predicted values ​​predicted by the prediction unit 102. The method of drug addition refers to 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 constitutes changing or adjusting the method of drug addition. In addition, changing the type or formulation of the drug to be added also constitutes changing the method of drug addition.

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

[0123] Next, the control unit 10 determines 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 drug injection rate adjustment processing (S63). The drug rate adjustment processing described above will be explained later. After that, 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 (for example, 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 processing shown in Figure 3 (S65). Next, the control unit 10 resets and starts the first timer t1 (S66). After that, 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. In other words, the instruction processing and drug injection rate adjustment processing are performed alternately. This prevents the execution of the instruction processing from affecting the drug injection rate adjustment processing.

[0127] Figure 16 is a flowchart showing an example of the drug concentration adjustment process. At the start of the process in Figure 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] Figure 17 is a flowchart showing an example of the drug injection rate reduction effect determination 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 drug addition at the time the process in S81 is performed.

[0129] Next, the adjustment unit 107 reduces the drug injection rate (S82). The reduction in the drug injection rate can be predetermined. 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 method of drug addition has been changed by the process in S82. The second measurement data is measured after sufficient time has elapsed since the drug injection rate was reduced in S82, so that the effect appears in the measurement data. Hereafter, 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). Then, the prediction unit 102 predicts the water content from the measurement data measured after the drug injection rate was returned to its original value 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 method has been returned to the method immediately before S82 by the process in S84. After that, the process in Figure 17 is completed, and the process returns to the original process in Figure 16 and proceeds to step S72.

[0131] Furthermore, the third measurement data, like the second measurement data, is measured after sufficient time has elapsed for the effect of changing the drug injection rate to become apparent in the measurement data. This time may be the same as the time (Δt) for the second measurement data.

[0132] In step S72, the adjustment unit 107 determines whether the predicted moisture content decreased or remained unchanged by adjusting the drug injection rate based on the first to third predicted values ​​calculated in S71 (S72). Normally, reducing the drug injection rate increases the moisture content, so the result of the determination in S72 is often NO. However, for example, if the drug injection rate at the start of the process in Figure 16 is too high, the predicted moisture content may decrease by adjusting the drug injection rate. In such cases, the result of the determination in S72 is YES.

[0133] If the predicted value in step S72 decreases or remains unchanged (YES in S72), the adjustment unit 107 adjusts the manner 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 the supply device that supplies the drug to the flocculator 5, or by controlling the supply device via another device such as the control device 3. The same applies to S76, which will be described later.

[0134] Thus, the processes in S71 to S73 are repeated until NO is determined in S72. The processes in S71 to S73 can be described as a process that gradually reduces the drug injection rate by a predetermined reduction range until a decrease in the predicted moisture content can no longer be expected.

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

[0136] Figure 18 is a flowchart showing an example of the drug injection rate increase effect determination 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 drug addition at the time the process in S91 is performed.

[0137] Next, the adjustment unit 107 increases the drug injection rate (S92). The amount of increase in the drug injection rate can be predetermined. For example, the adjustment unit 107 may increase the drug injection rate by the same amount as in S82 in Figure 17.

[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 method of drug addition has been changed by the process in S92. The second measurement data is measured after sufficient time has elapsed since increasing the drug injection rate in S92 for that effect to appear in the measurement data. For example, the second measurement data may be measured after a time (Δt) has elapsed since increasing the drug injection rate in step S92, similar to S83 in Figure 17.

[0139] Next, the adjustment unit 107 returns the drug injection rate to the value before it was increased in S92 (S94). Subsequently, the prediction unit 102 predicts the water content from the measurement data measured after the drug injection rate was returned to its original value 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 method has been returned to the method immediately before step S42 by the process in step S94. After that, the process in Figure 18 is completed, and the process returns to the original process in Figure 16 and proceeds to step S75.

[0140] In step S75, the adjustment unit 107 determines whether the predicted water content has decreased by adjusting the drug injection rate based on the first to third predicted values ​​calculated in S74 (S75). If the predicted water content increases or remains unchanged (NO in S75), the process in Figure 16 ends and the process returns to the original state.

[0141] On the other hand, if the predicted water content decreases (YES in S75), the adjustment unit 107 adjusts the manner in which the drug is added (S76). More specifically, the adjustment unit 107 increases the drug injection rate. Then, the process returns to step S74.

[0142] Thus, the process from S74 to S76 is repeated until NO is determined in S75. The process from S74 to S76 can be described as a process in which the drug injection rate is gradually increased by a predetermined reduction amount until a decrease in the predicted moisture content can no longer be expected.

[0143] Then, the adjustment unit 107 repeats the processes in S71 to S73 until it is determined to be NO in S72, and then repeats the processes in S74 to S76, thereby adjusting the drug injection rate to a value that minimizes the water content and is not excessive.

[0144] [Embodiment 6] Further embodiments of the present invention will be described with reference to Figures 19 to 21. The control system 100 according to this embodiment differs from the control system 100 shown in Figure 2 in the configuration of the information processing device 1, but the other configurations are the same.

[0145] Figure 19 is a block diagram showing an example of the main components 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 Figure 14 in that the instruction unit 103 has been renamed to the first instruction unit 103 (control unit for the dewatering machine) and a second instruction unit 108 (control unit for the stirring blade) is also provided, but the other components are the same.

[0146] The second instruction unit 108 provides instructions regarding the stirring blade 52 to the flocculator control device 3a (stirring blade control unit) via the communication unit 12. In this embodiment, the acquisition unit 101 acquires measurement data of the size of the 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 dewatering machine control device 3b (dewatering machine control unit) to control the rotation speed of the stirring 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 falls outside the sixth predetermined range, the first indicator unit 103 and the adjustment unit 107 stop operating. This prevents the operation of the first indicator unit 103 and the adjustment unit 107 from being adversely affected by the flock size falling outside the sixth predetermined range. Note that the appropriate range and the sixth predetermined range may be the same or different.

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

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

[0150] If the size of the flocs in step S102 is smaller than the appropriate range, the second instruction unit 108 instructs the flocculator control device 3a to reduce the rotational speed of the stirring blade 52 by a predetermined amount (for example, 1 revolution / minute). After that, the instruction process is terminated. By periodically repeating steps S101 to S103, the size of the flocs can be gradually increased until it is finally within the appropriate range.

[0151] On the other hand, if the size of the flocs in step S102 is larger than the appropriate range, the second instruction unit 108 instructs the flocculator control device 3a to increase the rotational speed of the stirring blade 52 by a predetermined amount (for example, 1 revolution / minute). After that, the instruction process is terminated. By periodically repeating steps S101, S102, and S104, the size of the flocs is gradually reduced and eventually brought within the appropriate range.

[0152] Figure 21 is a flowchart showing an example of the processing performed by the control unit 10 in the information processing device 1 with the above configuration. The flowchart in Figure 21 differs from the flowchart in Figure 15 in that step S111 is added between steps S61 and S62, but the other processing is the same. Note that the processing in Figure 21 is performed in parallel with the processing in Figure 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 allows the operation of the first indicator unit 103 and the adjustment unit 107 to be stopped if 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 dewatered cake at a given time using a machine learning-based prediction model 111, but it is not limited to this. For example, the prediction unit 102 may predict the moisture content of the dewatered cake based on a predetermined calculation formula. Also, in the above embodiment, the information processing device 1 and the control device 3 are separate, but they may be integrated.

[0155] [Examples of implementation using software] The functions of the information processing device 1 (hereinafter referred to as "the device") are programs that cause the device to function as a computer, and these programs can be realized by programs that cause each control block of the device (especially each part included in the control unit 10) to function as a computer.

[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., memory) as hardware for executing the program. By executing the program using this control device and storage device, the functions described in each of the embodiments are realized.

[0157] The above program may be recorded on one or more computer-readable recording media, not temporary ones. These recording media may or may not be provided by the above device. In the latter case, the program may be supplied to the above device via any wired or wireless transmission medium.

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

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

[0160] The present invention is not limited to the embodiments described above, 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 Control device for flocculator (chemical control unit, agitator blade control unit) 3b Dehydrator control device (dehydrator control unit) 5. Flocculator 9 Dehydrator 10 Control Unit 11 Storage section 51 Coagulation tank 52 Agitator blades 53 Motor 54 Inspection window 55 Sludge inlet 56 Drug input slot 57 Outlet 71 Lighting equipment 72 Imaging device 91 Outer shell screen 92 Screw 93 Sludge inlet 94 Liquid outlet 95 Dehydrated cake outlet 100 control systems 101 Acquisition Department 102 Prediction Unit, First Prediction Unit 103 Indicator unit (control unit), first indicator unit (control unit for dehydrator) 104 Second Prediction Section 105 Instruction Unit (Control Unit) 106 Update section 107 Adjustment Unit (Drug Control Unit) 108 Second instruction unit (control unit for stirring blades) 111 Predictive Models 112 Estimated Models

Claims

1. An acquisition unit that acquires measurement data including at least the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid discharged from a coagulation tank to which a chemical agent for coagulating the suspended solids is added, while conveying the liquid with a screw, A first prediction unit uses the measurement data acquired by the acquisition unit to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data to the time of dewatering. A control device comprising: a control unit that determines whether the flow rate of the liquid acquired by the acquisition unit is within a first predetermined range, and if the flow rate of the liquid is outside the 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 if the flow rate of the liquid is within the first predetermined range, a control unit that determines whether the moisture content of the dewatered cake predicted by the first prediction unit is within a second predetermined range, and if the moisture content of the dewatered cake is outside the second predetermined range, controls the rotation speed of the screw so that the moisture content of the dewatered cake is within the second predetermined range.

2. The system further includes a second prediction unit that predicts the time to stop the operation of the dewatering machine based on the measurement data acquired by the acquisition unit, The control unit, If the flow rate of the liquid is within the first predetermined range, and the predicted time predicted by the second prediction unit is outside the third predetermined range, the rotation speed of the screw is controlled so that the predicted time falls within the third predetermined range, and The control device according to claim 1, wherein if 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 dewatered cake is outside the second predetermined range, the rotation speed of the screw is controlled so that the moisture content of the dewatered cake falls within the second predetermined range.

3. An acquisition unit that acquires measurement data including at least the flow rate of the liquid supplied to a screw press type dewatering machine that dewaters the liquid discharged from a coagulation tank to which a chemical agent for coagulating the suspended solids is added, while conveying the liquid with a screw, A first prediction unit uses the measurement data acquired by the acquisition unit to predict the moisture content of the dewatered cake discharged from the dewatering machine at a time when the liquid has remained in the dewatering machine for a period of time from the time of measurement of the measurement data to the time of dewatering. A second prediction unit predicts the time to stop the operation of the dewatering machine based on the measurement data acquired by the acquisition unit, A control device comprising: a control unit that controls the rotational speed of the screw such that the flow rate of the liquid acquired by the acquisition unit falls within a first predetermined range, the moisture content of the dewatered cake predicted by the first prediction unit falls within a second predetermined range, and the predicted time predicted by the second prediction unit falls within a third predetermined range.

4. The measurement data acquired by the acquisition unit includes measurement data related to the operation of the dewatering machine. The first prediction unit predicts the moisture content of the dehydrated cake using a prediction model, The prediction model is a prediction model that has been learned with the measurement data acquired by the acquisition unit as the explanatory variable and the estimated value by an estimation model for the moisture content of the dewatered cake discharged from the dewatering machine at the time when the residence time has elapsed from the time of measurement of the measurement data as the dependent variable. The control device according to any one of claims 1 to 3, wherein the estimation model is an estimation model learned with measurement data relating to the operation of the dewatering machine as explanatory variables and the moisture content of the dewatered cake discharged from the dewatering machine at the time of measurement of the measurement data as the dependent variable.

5. The second prediction unit is, The following are obtained: a first period from the start time when the dewatering machine starts operating to a first time; a measured value of the processing amount per unit rotation of the screw of the dewatering machine during the first period; and a measured value of the rotational speed of the screw at the first time. The following are obtained: a measurement of the processing amount per unit rotation of the screw during the first period, which is the average value of the measurement of the processing amount per unit rotation of the screw over a predetermined number of past days; and a measurement of the processing amount per unit rotation of the screw during the operating period from the start time of operation to the stop time when the dewatering machine is stopped, which is the average value of the measurement of the processing amount over the predetermined number of past days. The control device according to claim 2 or 3, which uses a measured value of the processing amount per unit rotation of the screw during the first period, the average value of the measured values ​​of the processing amount per unit rotation of the screw during the first period over a predetermined number of past days, the average value of the measured values ​​of the processing amount per unit rotation of the screw during the operating period over a predetermined number of past days, and a measured value of the rotational speed of the screw at a first time to predict the operating period from a target value of the processing amount to be reached during the operating period.

6. The control device according to any one of claims 1 to 3, wherein the control unit issues an alarm if the moisture content of the dewatered cake predicted by the first prediction unit falls outside a fourth predetermined range which includes the second predetermined range.

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

8. The control device according to any one of claims 1 to 3, wherein the control unit controls the rotational speed of the screw by increasing or decreasing the rotational speed of the screw by a predetermined amount and doing so periodically.

9. The control unit includes a control unit for the dehydrator that controls the rotation speed of the screw, and a control unit for the chemicals that controls the addition of the chemicals. The control unit alternately operates the dehydrator control unit and the chemical control unit. The control device according to any one of claims 1 to 3, wherein the drug control unit adjusts the manner of adding the drug 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 adding the drug 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 adding the drug is changed.

10. The control unit further includes a control unit for the stirring blade that controls the rotational speed of the stirring blade in the coagulation tank, The control unit for the stirring blade operates in parallel with the operation of the control unit for the dewatering machine and the control unit for the chemicals. The acquisition unit further acquires measurement data of the size of the flocs formed in the coagulation tank. The control device according to claim 9, wherein the control unit stops the operation of the dehydrator control unit and the chemical control unit when the size of the floc 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 described in claim 1, wherein the control program causes the 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 described in claim 3, wherein the first prediction unit, the second prediction unit, and the control unit are the computer.

13. A step of acquiring measurement data that includes at least the flow rate of the liquid supplied to a screw press type dewatering machine, which dewaters the liquid discharged from a coagulation tank to which a chemical agent for coagulating the suspended solids is added, while transporting the liquid with a screw, A first prediction step in which, using the measurement data acquired in the acquisition step, predicts the moisture content of the dewatered cake discharged from the dewatering machine at the time when the residence time during which the liquid remains in the dewatering machine has elapsed from the time of measurement of the measurement data, A control method for a control device, comprising: a control step which determines whether the flow rate of the liquid obtained in the acquisition step is within a first predetermined range, and if the flow rate of the liquid is outside the 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 if the flow rate of the liquid is within the first predetermined range, determines whether the moisture content of the dewatered cake predicted in the first prediction step is within a second predetermined range, and if the moisture content of the dewatered cake is outside the second predetermined range, controls the rotation speed of the screw so that the moisture content of the dewatered cake is within the second predetermined range.

14. A step of acquiring measurement data that includes at least the flow rate of the liquid supplied to a screw press type dewatering machine, which dewaters the liquid discharged from a coagulation tank to which a chemical agent for coagulating the suspended solids is added, while transporting the liquid with a screw, A first prediction step in which, using the measurement data acquired in the acquisition step, predicts the moisture content of the dewatered cake discharged from the dewatering machine at the time when the residence time during which the liquid remains in the dewatering machine has elapsed from the time of measurement of the measurement data, A second prediction step predicts the time to stop the operation of the dewatering machine based on the measurement data acquired in the acquisition step, A control method for a control device, comprising: a control step of controlling the rotation speed of the screw such that the flow rate of the liquid acquired in the acquisition step falls within a first predetermined range, the moisture content of the dewatered cake predicted in the first prediction step falls within a second predetermined range, and the predicted time predicted in the second prediction step falls within a third predetermined range.

Images