Information processing device, water treatment system, sludge state determination method, and sludge state determination program

Abstract

To appropriately determine the state of flocculated sludge so that a chemical injection rate can be appropriately set without being affected by the presence or absence of the occurrence of white turbidity.SOLUTION: An information processing device (1) includes a sludge image acquisition unit (101) configured to acquire a sludge image captured by an imaging device for flocculated sludge in which a plurality of flocs formed by flocculating solid suspended matter in the sludge overlap each other, a first image acquisition unit (102) configured to acquire a first image by performing edge processing and then binarization processing on the sludge image and further performing closing processing, and a determination unit (104) configured to determine a state of the flocculated sludge using the first image.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] A conventional technique involves adding a chemical such as a flocculant to a liquid to be treated, such as sewage sludge, and stirring the liquid to flocculate suspended solids to form flocs, and then dewatering the flocculated sludge, which is an aggregate of these flocs, to obtain dewatered sludge. In order to stably dewater sludge, it is essential to properly understand the state of the flocculated sludge, including whether flocs of an appropriate size have been formed. Among the techniques for understanding the state of flocs, there is one that uses images of the flocculated sludge, including flocs, taken with a camera (see Patent Document 1, etc.). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2023-163696 [Patent Document 2] Japanese Patent Publication No. 2022-081219 Summary of the Invention [Problem to be solved by the invention]

[0004] In the process of developing technology to grasp the state of flocs from images of flocculated sludge, the inventors discovered a problem in that it is sometimes difficult to distinguish from flocs by image processing the turbidity that occurs in the interstitial water between flocs due to factors such as a lack of chemicals or the influence of turbid components contained in the sludge or chemicals.If the turbidity is erroneously determined to be flocs in image processing, it becomes impossible to appropriately set the amount of chemicals to be added (chemical dosing rate), which causes the problem of not being able to properly dewater the sludge.

[0005] An object of one aspect of the present invention is to appropriately determine the state of flocculated sludge so that the chemical feeding rate can be appropriately set regardless of whether or not cloudiness occurs. [Means for solving the problem]

[0006] In order to solve the above problem, an information processing device according to one embodiment of the present invention includes a sludge image acquisition unit that acquires a sludge image captured by an imaging device of flocculated sludge, which is formed by the aggregation of solid floating matter in the sludge and consisting of multiple overlapping flocs; a first image acquisition unit that performs edge processing on the sludge image, binarizes it, and then performs closing processing on it to acquire a first image; and a determination unit that determines the state of the flocculated sludge using the first image.

[0007] Furthermore, a sludge condition determination method according to one embodiment of the present invention is a sludge condition determination method executed by one or more information processing devices, and includes a sludge image acquisition step of acquiring an image of flocculated sludge, which is formed by aggregating solid floating matter in the sludge and consisting of multiple overlapping flocs, as a sludge image; a first image acquisition step of performing edge processing on the sludge image, binarizing the sludge image, and further performing closing processing to obtain a first image; and a determination step of determining the condition of the flocculated sludge using the first image. [Effects of the Invention]

[0008] According to one aspect of the present invention, the state of flocculated sludge can be appropriately determined so that the chemical feeding rate can be appropriately set regardless of whether or not cloudiness occurs. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of a main configuration of an information processing device according to an embodiment of the present invention; [Figure 2] FIG. 2 is a diagram illustrating a configuration example of a water treatment system including the information processing device. [Figure 3] 4 is a diagram showing an example of a sludge image acquired by a sludge image acquisition unit of the information processing device. FIG. [Figure 4] 3A to 3C are diagrams showing examples of images created by various processes in a first image acquisition unit of the information processing device. [Figure 5] 4 is a diagram showing an example of a second image acquired by a second image acquisition unit of the information processing device. FIG. [Figure 6] 6A to 6C are diagrams showing other examples of a sludge image, a first image, and a second image acquired by the sludge image acquisition unit, the first image acquisition unit, and the second image acquisition unit, respectively. [Figure 7] 10A and 10B are diagrams showing still other examples of a sludge image, a first image, and a second image acquired by the sludge image acquisition unit, the first image acquisition unit, and the second image acquisition unit, respectively. [Figure 8] 10 is a flowchart illustrating an example of an index value calculation process executed by the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, one embodiment of the present invention will be described with reference to FIGS.

[0011] (Water treatment system) An overview of a water treatment system 100 according to this embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the water treatment system 100. The water treatment system 100 is a system for separating a liquid to be treated into suspended solids and a liquid component, and as shown in Fig. 2, includes an information processing device 1, a control device 3, a flocculator 5, an addition device 6, and a dehydrator 9. In the following, an example will be described in which the liquid to be treated is sludge generated in biological treatment of sewage or the like. Sludge is a liquid containing suspended solids and can also be called a slurry.

[0012] The flocculator 5 is a device that aggregates suspended solids in sludge to form flocs and obtain aggregated sludge. The flocculator 5 in Fig. 2 is equipped with a coagulation tank (also called an agitation tank) 51 (tank), an agitator blade 52, a motor 53, and an inspection window 54 (window). The sludge in the coagulation tank 51 is agitated by rotating the agitator blade 52 using the motor 53, so the flocculator 5 can also be said to be an agitation device. The flocculator 5 is also provided with a sludge inlet 55, a chemical agent inlet 56, and a discharge outlet 57.

[0013] Furthermore, a photographing device 72 and a lighting device 71 for photography are attached to the inspection window 54. The photographing device 72 may be any device capable of at least taking still images. It is preferable that the coagulation tank 51 is opaque so that the way light hits the flocs does not change during operation of the water treatment system 100. It is also preferable that the photographing device 72 and the lighting device 71 are housed in a light-blocking dark box with an opening on the inspection window 54 side, as in the example of Figure 2. The photographing device 72 may be used from above the liquid surface. Alternatively, the photographing device 72 may be submerged in water to take photographs.

[0014] The dehydrator 9 is disposed downstream of the flocculator 5 and is a device for dehydrating the flocculated sludge discharged from the flocculator 5. The dehydrator 9 in FIG. 2 is a screw press type dehydrator equipped with an outer screen 91 and a screw 92. The dehydrator 9 is also provided with a sludge inlet 93, a filtrate outlet 94, and a dehydrated cake outlet 95. Of course, the dehydrator 9 is not limited to the screw press type as long as it can dehydrate the flocculated sludge. For example, a centrifugal dehydrator, a filter press dehydrator, or a belt press dehydrator may also be used.

[0015] In the water treatment system 100, the sludge to be treated is continuously or intermittently supplied from a sludge inlet 55 into the coagulation tank 51 of the flocculator 5 by a supply device (not shown). The supply rate of the sludge may be automatically controlled by the supply device or its control device according to the sludge treatment rate by the flocculator 5 and the dehydrator 9.

[0016] Then, under the control of the control device 3, the adding device 6 feeds a chemical (including at least a flocculant) for flocculating the sludge into the coagulation tank 51 through the chemical inlet 56. In this state, the motor 53 is driven to rotate the agitator blade 52, which agitates the sludge and the chemical in the coagulation tank 51 and forms flocs. The flocculated sludge, which is a mixture of the formed flocs and water contained in the sludge, is then discharged through the outlet 57. The chemical may be added in advance to the sludge before it is fed into the flocculator 5 through the sludge inlet 55.

[0017] During this process of forming flocs, the image capturing device 72 captures an image. Note that this image shows flocculated sludge containing multiple flocs and interstitial water present in the gaps between the multiple flocs, and therefore this image will be referred to as a sludge image hereinafter. Multiple flocs are shown overlapping each other in the sludge image, making it difficult to calculate the number of flocs and the area of ​​each individual floc. For this reason, the information processing device 1 detects and analyzes the background areas, rather than the flocs, from the sludge image to calculate an index value indicating the state of floc formation.

[0018] Subsequently, this flocculated sludge is supplied into the outer body screen 91 from the sludge inlet 93 of the dehydrator 9. In the dehydrator 9, the flocculated sludge is dehydrated under pressure by the screw 92, and the filtrate is discharged from the filtrate outlet 94. After the flocculated sludge is dehydrated, the dehydrated cake is discharged from the dehydrated cake outlet 95.

[0019] The control device 3 controls at least one of the amount of chemical added by the addition device 6 and the stirring speed in the flocculator 5, so that the flocs have an appropriate size, according to the index value calculated by the information processing device 1 and indicating the state of floc formation. Details of this control will be described later. The control device 3 may also control other devices in the water treatment system 100. The stirring speed can also be referred to as stirring intensity.

[0020] As described above, the water treatment system 100 includes the addition device 6 that adds an agent that coagulates suspended solids to the sludge in the coagulation tank 51, the flocculator 5 that agitates the sludge in the coagulation tank 51, the photographing device 72 that photographs the flocs in the coagulation tank 51 through the inspection window 54, the information processing device 1 that calculates an index value that indicates the floc formation state from the image taken by the photographing device 72, and the control device 3 that controls at least one of the amount of agent added by the addition device 6 and the agitation speed according to the calculated index value.

[0021] As described above, the information processing device 1 detects and analyzes background regions, rather than flocs, from a sludge image to calculate an index value indicating the floc formation state. Therefore, an index value accurately indicating the floc formation state can be calculated from a sludge image in which multiple flocs overlap. As a result, the floc formation state, and ultimately the state of the flocculated sludge, can be accurately determined from the index value. Furthermore, controlling the amount of chemical agent added and the agitation speed are both effective for changing the size of flocs. Therefore, the water treatment system 100 can automatically improve the floc formation state while treating sludge, and can stably produce flocs of an appropriate size.

[0022] (Information processing device) A more detailed configuration of the information processing device 1 will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the main configuration of the information processing device 1. As shown in Fig. 1, the information processing device 1 includes a control unit 10 that controls each unit of the information processing device 1, and a storage unit 11 that stores various data used by the information processing device 1. The information processing device 1 also includes a communication unit 12 that enables the information processing device 1 to communicate with other devices (e.g., the control device 3), an input unit 13 that accepts input to the information processing device 1, and an output unit 14 that enables the information processing device 1 to output information.

[0023] The control unit 10 also includes a sludge image acquisition unit 101, a first image acquisition unit 102, a second image acquisition unit 103, a determination unit 104, and an instruction unit 105. The sludge image acquisition unit 101 acquires a sludge image from the imaging device 72 via the communication unit 12. The sludge image acquisition unit 101 sends the acquired sludge image to the first image acquisition unit 102 and the second image acquisition unit 103.

[0024] The first image acquisition unit 102 performs edge processing on the sludge image from the sludge image acquisition unit 101, then performs binarization processing and closing processing to acquire a first image divided into a floc region and a background region. If the sludge image is a color image, it is desirable to convert the sludge image into a grayscale image before edge processing. The first image acquisition unit 102 sends the acquired first image to the determination unit 104.

[0025] Edge processing is a process for detecting boundaries between bright and dark areas in an image, specifically, a process for detecting locations where gray values ​​(brightness values) change suddenly. Examples of edge processing include a Sobel filter and a Laplacian filter. Binarization is a process for assigning each pixel in an image to either white or black based on a threshold value. The binarization process may be static binarization, in which the threshold value is set in advance, or dynamic binarization, in which a threshold value is set for each small area in the image.

[0026] Closing processing is a process that combines expansion processing and erosion processing, and after performing expansion processing N times (N is an integer greater than or equal to 1) on a binarized image, erosion processing is performed the same number of times. By performing closing processing, noise can be removed without significantly changing the size of the binarized area. Note that the first image acquisition unit 102 may further perform expansion processing after closing processing to acquire the first image.

[0027] The second image acquisition unit 103 performs binarization processing on the sludge image from the sludge image acquisition unit 101 to acquire a second image divided into a floc region and a background region. The second image acquisition unit 103 sends the acquired second image to the determination unit 104. If the sludge image is a color image, it is desirable that the sludge image be converted into a grayscale image before being binarized. The sludge image, the first image, and the second image will be described later with reference to FIGS. 3 to 5.

[0028] The determination unit 104 determines the state of the flocculated sludge using either or both of the first image from the first image acquisition unit 102 and the second image from the second image acquisition unit 103. The determination unit 104 sends the determination result to the instruction unit 105.

[0029] In this embodiment, the determination unit 104 calculates an index value indicating the floc formation state as a determination result of the state of the flocculated sludge. Specifically, the determination unit 104 detects a background region using either or both of the first and second images, and analyzes multiple small regions that make up the background region to calculate the index value. For example, the determination unit 104 counts the number of small regions by regarding a continuous region made up of adjacent pixels among the pixels included in the background region as one small region. The determination unit then calculates the index value by dividing the total area of ​​the background region by the number of small regions, i.e., the average area of ​​the small regions. Note that details of the index value are described in the above-mentioned Patent Document 2, and therefore will not be described here.

[0030] The instruction unit 105 issues various instructions to the control device 3 via the communication unit 12. Based on the various instructions, the control device 3 controls various devices. Note that the instruction unit 105 may also control various devices via the communication unit 12. In this case, the control device 3 can be omitted.

[0031] In this embodiment, the instructing unit 105 instructs the control device 3 to maintain an appropriate floc size based on the determination result from the determining unit 104. The control device 3 controls, for example, at least one of the amount of chemical added by the adding device 6 in the water treatment system 100 and the rotation speed of the motor 53 based on the instruction from the instructing unit 105.

[0032] (Regarding the sludge image, the first image, and the second image) Fig. 3 is a diagram showing an example of a sludge image A1 acquired by the sludge image acquisition unit 101. In the sludge image A1 shown in Fig. 3, the flock region is brighter in color than the background region, and the interstitial water present in the gaps between multiple flocks is cloudy. In addition, the flock region contains many irregularities.

[0033] FIG. 4 is a diagram showing examples of images a10 to a13 created by various processes in the first image acquisition unit 102. Image a10 shown in FIG. 4 is an image obtained by converting the sludge image A1 shown in FIG. 3 into a grayscale image and then performing edge processing. In the example of FIG. 4, the conversion coefficients to grayscale are R=299, G=587, and B=114. In image a10 shown in FIG. 4, the edge regions are brighter in color than the other regions. Furthermore, the flock region includes many edge regions.

[0034] Image a11 shown in Figure 4 is an image obtained by binarizing image a10. In the example of Figure 4, dynamic binarization processing was performed. In image a11 shown in Figure 4, the edge region is white and the other region is black. The boundary between the edge region and the other region, which was unclear in image a10, is clearly recognizable in image a11.

[0035] Image a12 shown in Figure 4 is an image that has undergone closing processing on image a11. Compared to image a11, image a12 has noise removed, resulting in edge regions that are connected and wider white regions that resemble flocked regions.

[0036] Image a13 shown in Fig. 4 is an image obtained by expanding image a12. Comparing sludge image A1 shown in Fig. 3 with image a13 shown in Fig. 4, it can be seen that the flock region in image a13 is almost white. Therefore, image a13 is the first image a1 divided into a flock region and a background region.

[0037] Fig. 5 is a diagram showing an example of a second image acquired by the second image acquisition unit 103. The second image a2 shown in Fig. 5 is an image obtained by converting the sludge image A1 shown in Fig. 3 into grayscale and then performing binarization processing. The conversion coefficient to grayscale in the example of Fig. 5 is the same as the conversion coefficient to grayscale in the example of Fig. 4. The threshold value for the binarization processing is set to 104.

[0038] 3 to 5, it can be seen that on the left side of the sludge image A1, an area 300 of interstitial water reflecting a turbidity in a color tone similar to that of flocs appears as a black area 301 in the first image a1, while appearing as a white area 302 in the second image a2. Therefore, compared to the second image a2, the first image a1 shows an image in which the boundary between the interstitial water and flocs is closer to the actual state of sludge when the interstitial water is turbid.

[0039] Furthermore, the index value calculated by the determining unit 104 using the first image a1 was 2556 pixels, a value close to the actual floc formation state. On the other hand, the index value calculated by the determining unit 104 using the second image a2 was 517 pixels, a value significantly different from the actual floc formation state. Therefore, when determining the state of flocculated sludge using the first image a1, the determining unit 104 can appropriately determine the state of the flocculated sludge.

[0040] From this, it can be understood that the determination unit 104 may determine whether the interstitial water is cloudy or not using the first image a1 and the second image a2. For example, the determination unit 104 may determine that the interstitial water is cloudy when the index value calculated using the first image a1 is greater than the index value calculated using the second image a2 by a predetermined value (for example, 400 pixels). In this case, the state of the flocculated sludge can be determined more specifically.

[0041] Incidentally, when the interstitial water is cloudy, it may be that the amount of chemical added by the addition device 6 is insufficient. Therefore, the determination unit 104 may instruct the control device 3 via the instruction unit 105, and the control device 3 may control the addition device 6 to increase the amount of chemical added.

[0042] 4, the first image acquisition unit 102 performed the edge processing using a Sobel filter. By using a Sobel filter, edges are emphasized while noise is reduced, so that the first image a1 can be obtained as being closer to the actual state of the sludge, and the state of the flocculated sludge can be more appropriately determined.

[0043] 4, the first image acquisition unit 102 performs expansion processing on the image a12 that has been subjected to closing processing to acquire the first image a1 (a13). This makes it possible to obtain the first image a1 in which the flocs and interstitial water are well separated, thereby making it possible to more appropriately determine the state of the flocculated sludge.

[0044] Fig. 6 is a diagram showing another example of a sludge image B1, a first image b1, and a second image b2 respectively acquired by the sludge image acquisition unit 101, the first image acquisition unit 102, and the second image acquisition unit 103. The example shown in Fig. 6 shows a case where the interstitial water is not cloudy.

[0045] 6, it can be seen that the boundary between the interstitial water and the flocs in the second image b2 is closer to the actual sludge state than in the first image b1. The index value calculated by the determining unit 104 using the first image b1 was 450 pixels. On the other hand, the index value calculated by the determining unit 104 using the second image b2 was 401 pixels, which was closer to the actual floc formation state.

[0046] From this, it can be understood that the determining unit 104 may calculate the index value using the first image when it determines that the pore water is cloudy, and may calculate the index value using the second image when it determines that the pore water is not cloudy. In this case, the state of the flocculated sludge can be accurately grasped without being affected by the cloudiness of the interstitial water.

[0047] 7 is a diagram showing still another example of a sludge image C1, a first image c1, and a second image c2 respectively acquired by the sludge image acquisition unit 101, the first image acquisition unit 102, and the second image acquisition unit 103. The example shown in FIG. 7 shows a case where the interstitial water is not cloudy.

[0048] Referring to Figure 7, the floc area 310 on the right side of the sludge image C1 appears as an area 311 that is unclear from the black area in the first image c1, while it appears as an area 312 that is clearly separated from the black area in the second image c2.

[0049] Meanwhile, compared to the interstitial water region 320 on the left side of the sludge image C1, the interstitial water region 321 in the first image c1 is of approximately the same size, while the interstitial water region 322 in the second image c2 is smaller. In this case, the index value calculated by the determining unit 104 using the second image c2 was 632 pixels. On the other hand, the index value calculated by the determining unit 104 using the first image c1 was 779 pixels, a value close to the actual state of floc formation.

[0050] Thus, even when the interstitial water is not cloudy, the boundary between the interstitial water and the flocs may be closer to the actual state of the sludge in the first image c1 than in the second image c2. In this case, the determining unit 104 can appropriately determine the state of the flocculated sludge by determining the state of the flocculated sludge using such first image c1. Furthermore, the determining unit 104 obtains an index value indicating the state of floc formation by focusing on the background region rather than the flocs, and therefore can accurately grasp the state of floc formation, and therefore the state of the flocculated sludge, from the index value.

[0051] (Index value calculation process) The flow of the index value calculation process (sludge state determination method) executed by the information processing device 1 will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the index value calculation process executed by the information processing device 1. The processes of S1 to S9 described below are performed continuously while the water treatment system 100 is in operation. Furthermore, while the water treatment system 100 is in operation, the imaging device 72 takes images at predetermined time intervals, and the captured images are acquired by the sludge image acquisition unit 101 of the information processing device 1 as sludge images.

[0052] In S1, the sludge image acquisition unit 101 acquires a sludge image from the photographing device 72 via the communication unit 12 (sludge image acquisition step). Then, in S2, the first image acquisition unit 102 performs edge processing on the sludge image acquired in S1, then performs binarization processing, and further performs closing processing to acquire a first image divided into a flock region and a background region (first image acquisition step). In S3, the second image acquisition unit 103 performs binarization processing on the sludge image acquired in S1 to acquire a second image divided into a flock region and a background region. Note that S3 may be executed before S2 or may be executed simultaneously with S2.

[0053] In S4, determination unit 104 detects a background region for each of the first image and the second image, and calculates an index value by analyzing a plurality of small regions that make up the background region. In S5, determination unit 104 determines whether the index value calculated using the first image is greater than or equal to a predetermined value than the index value calculated using the second image.

[0054] If the index value calculated using the first image in S5 is greater than or equal to the index value calculated using the second image by a predetermined value (Yes in S5), the process proceeds to S6. On the other hand, if the index value calculated using the first image in S5 is less than the index value calculated using the second image by a predetermined value (No in S5), the process proceeds to S7.

[0055] In S6, the determination unit 104 determines that the interstitial water is cloudy, sets the index value calculated using the first image as the determination result (determination step), and proceeds to S8. On the other hand, in S7, the determination unit 104 determines that the interstitial water is not cloudy, sets the index value calculated using the second image as the determination result, and proceeds to S8.

[0056] In S8, the instruction unit 105 determines whether or not the control device 3 needs to control the equipment based on the index value of the determination result determined by the determination unit 104. Note that Fig. 8 illustrates an example in which the equipment to be controlled is the motor 53, that is, an example in which the floc size is adjusted by adjusting the stirring speed. Of course, the instruction unit 105 may also instruct the control device 3 to adjust the floc size by controlling the addition device 6 or other devices.

[0057] If it is determined in S8 that control is not required (No in S8), the processing in Fig. 8 ends. On the other hand, if it is determined that control is required (Yes in S8), the processing proceeds to S9. Note that the criteria for determining whether control is required may be determined in advance, and for example, the instruction unit 105 may determine that control is required when the index value is outside a predetermined appropriate range.

[0058] In S9, the instruction unit 105 instructs the control device 3 to change the number of times the flocs are stirred per unit time. Specifically, the instruction unit 105 changes the number of times the flocs are stirred by instructing the control device 3 to change the rotation speed of the motor 53, and the process in Fig. 8 is then terminated. Note that the method for changing the rotation speed has already been described, and therefore the description will not be repeated here.

[0059] [Software implementation example] The functions of the information processing device 1 (hereinafter referred to as the "device") can be realized by a program for causing a computer to function as the device, and a program (sludge state determination program) for causing a computer to function as each control block of the device (particularly each part included in the control unit 10).

[0060] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program, thereby realizing the functions described in each of the above embodiments.

[0061] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0062] Furthermore, some or all of the functions of the control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of the present invention. In addition, the functions of the control blocks can also be realized by, for example, a quantum computer.

[0063] Furthermore, each process described in each of the above embodiments may be executed by AI (Artificial Intelligence). In this case, the AI ​​may run on the control device or on another device (for example, an edge computer or a cloud server).

[0064] 〔summary〕 The information processing device according to aspect 1 of the present invention includes a sludge image acquisition unit that acquires a sludge image captured by a photographing device of flocculated sludge, which is formed by the aggregation of solid floating matter in the sludge and consists of multiple overlapping flocs; a first image acquisition unit that performs edge processing on the sludge image, binarizes it, and then performs closing processing on it to acquire a first image; and a determination unit that determines the state of the flocculated sludge using the first image.

[0065] The information processing device according to aspect 2 of the present invention is in accordance with aspect 1 above, and may further include a second image acquisition unit that binarizes the sludge image to acquire a second image, and the determination unit may use the second image in addition to the first image to determine whether or not the interstitial water present in the gaps between the plurality of flocs is cloudy.

[0066] In an information processing device according to a third aspect of the present invention, in the above-mentioned second aspect, when the determination unit determines that the interstitial water is turbid, the determination unit may detect a background region of the flocs from the first image and analyze a plurality of small regions that make up the background region to calculate an index value that indicates the formation state of the flocs, while when the determination unit determines that the interstitial water is not turbid, the determination unit may detect a background region of the flocs from the second image and analyze a plurality of small regions that make up the background region to calculate an index value that indicates the formation state of the flocs.

[0067] In the information processing device according to aspect 4 of the present invention, in the above aspects 1 to 3, the determination unit may detect a background region of the flocs from the first image, and analyze a plurality of small regions constituting the background region to calculate an index value indicating the formation state of the flocs.

[0068] In the information processing device according to aspect 5 of the present invention, in any of aspects 1 to 4 above, the first image acquisition section may perform the edge processing using a Sobel filter.

[0069] In the information processing device according to aspect 6 of the present invention, in any of aspects 1 to 5 above, the first image acquisition unit may acquire the first image by performing an expansion process after performing the closing process.

[0070] In the information processing device according to aspect 7 of the present invention, in the above aspect 2, when the judgment unit determines that the interstitial water is cloudy, the judgment unit may instruct a control device that controls the amount of chemical added to the liquid to be treated to coagulate solid suspended matter to increase the amount of chemical added.

[0071] A water treatment system according to aspect 8 of the present invention includes an addition device that adds an agent that coagulates suspended solids to the liquid to be treated in a coagulation tank, an imaging device that photographs the coagulated sludge in the coagulation tank, an information processing device according to aspects 1 to 7 above that determines the state of the coagulated sludge from the images taken by the imaging device, and a control device that controls the amount of the agent added by the addition device depending on the state of the coagulated sludge.

[0072] A sludge condition determination method according to aspect 9 of the present invention is a sludge condition determination method executed by one or more information processing devices, and includes a sludge image acquisition step of acquiring an image of flocculated sludge, which is formed by flocculating solid floating matter in the sludge and consisting of multiple overlapping flocs, as a sludge image; a first image acquisition step of performing edge processing on the sludge image, binarizing it, and further performing closing processing on it, to obtain a first image; and a determination step of determining the condition of the flocculated sludge using the first image.

[0073] The information processing device according to any one of aspects 1 to 7 of the present invention may be realized by a computer. In this case, the sludge state determination program of the information processing device, which causes the computer to operate as each part (software element) of the information processing device, thereby realizing the information processing device on the computer, and the computer-readable recording medium on which the program is recorded, also fall within the scope of the present invention.

[0074] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of symbols]

[0075] 1. Information processing equipment 3. Control device 5 Flocculator 6 Addition device 9 Dehydrator 10 Control Unit 11 Storage section 12 Communications Department 13 Input section 14 Output section 51 Coagulation tank 52 Mixing blade 53 Motor 54 Inspection window 55 Sludge inlet 56 Drug inlet 57 Outlet 71 Lighting equipment 72 Imaging equipment 100 Water Treatment Systems 101 Sludge image acquisition unit 102 First image acquisition unit 103 Second image acquisition unit 104 Judgment section 105 Instruction section

Claims

1. a sludge image acquisition unit that acquires a sludge image taken by an image capture device of flocculated sludge, which is formed by flocculating solid suspended matter in the sludge and overlapping multiple flocs; a first image acquisition unit that performs edge processing on the sludge image, binarizes the sludge image, and then performs closing processing on the sludge image to acquire a first image; a determination unit that determines a state of the flocculated sludge using the first image.

2. a second image acquisition unit that performs binarization processing on the sludge image to acquire a second image; The information processing device according to claim 1 , wherein the determining unit determines whether or not interstitial water present in gaps between the plurality of flocs is cloudy by using the second image in addition to the first image.

3. The determination unit When it is determined that the interstitial water is cloudy, a background region of the flocs is detected from the first image, and a plurality of small regions constituting the background region are analyzed to calculate an index value indicating a formation state of the flocs; 3. The information processing device according to claim 2, wherein, when it is determined that the interstitial water is not cloudy, a background region of the flocs is detected from the second image, and a plurality of small regions constituting the background region are analyzed to calculate an index value indicating a formation state of the flocs.

4. The information processing device according to claim 1 , wherein the determination unit detects a background region of the flocs from the first image, and analyzes a plurality of small regions constituting the background region to calculate an index value indicating a formation state of the flocs.

5. The information processing device according to claim 1 , wherein the first image acquisition unit performs the edge processing using a Sobel filter.

6. The information processing apparatus according to claim 1 , wherein the first image acquisition unit acquires the first image by performing an expansion process after performing the closing process.

7. 3. The information processing device according to claim 2, wherein, when the determination unit determines that the interstitial water is cloudy, the determination unit instructs a control device that controls the amount of chemical added to the treated liquid to coagulate solid suspended matter to increase the amount of chemical added.

8. an adding device that adds an agent that coagulates suspended solids to the liquid to be treated in the coagulation tank; an imaging device for imaging the flocculated sludge in the flocculation tank; The information processing device according to claim 1 , wherein the state of the flocculated sludge is determined from the image captured by the imaging device; a control device that controls the amount of the chemical added by the adding device depending on the state of the flocculated sludge.

9. A sludge state determination method executed by one or more information processing devices, a sludge image acquisition step of acquiring, as a sludge image, an image of flocculated sludge formed by flocculating solid suspended matter in the sludge and overlapping a plurality of flocs; a first image acquisition step of performing edge processing on the sludge image, binarizing the sludge image, and then performing closing processing on the sludge image to acquire a first image; a determining step of determining the state of the flocculated sludge using the first image.

10. A sludge state determination program for causing a computer to function as the information processing device according to claim 1, the sludge state determination program causing a computer to function as the sludge image acquisition unit, the first image acquisition unit, and the determination unit.

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