Information processing device, water treatment system, sludge condition determination method, and sludge condition 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 apparatus, a water treatment system, a sludge state determination method, and a sludge state determination program.

Background Art

[0002] Conventionally, a technique has been used in which a chemical such as a flocculant is added to a liquid to be treated such as sewage sludge and stirred to aggregate solid suspended matter to form flocs, and the aggregated sludge, which is an aggregate of these flocs, is dehydrated to obtain dehydrated sludge. In order to perform sludge dehydration stably, it is essential to appropriately grasp the state of the aggregated sludge containing flocs, such as whether flocs of an appropriate size are formed. Among the techniques for grasping the state of flocs, there is a technique that uses an image obtained by photographing aggregated sludge containing flocs with a camera (Patent Document 1, etc.).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] [[ID=DBG]]During the process of developing a technique for grasping the state of flocs from an image of aggregated sludge, the inventors found that there is a problem in that it is sometimes difficult to distinguish, in terms of image processing, between the turbidity generated in the interstitial water between flocs due to causes such as insufficient chemicals and the influence of the turbidity components contained in the sludge and chemicals. If the turbidity is erroneously determined as a floc in image processing, there will be a problem that the chemical dosage (chemical injection rate) cannot be appropriately set and the sludge cannot be appropriately dehydrated.

[0005] One aspect of the present invention aims to appropriately determine the state of flocculated sludge so that the chemical injection rate can be appropriately set regardless of whether or not turbidity occurs. [Means for solving the problem]

[0006] To solve the above problems, an information processing device according to one aspect of the present invention includes: a sludge image acquisition unit that acquires a sludge image taken by a camera of aggregated sludge in which a plurality of flocs formed by agglomerating solid suspended matter in sludge overlap; a first image acquisition unit that performs edge processing on the sludge image, then binarization processing, and further closing processing to acquire a first image; and a determination unit that determines the state of the aggregated sludge using the first image.

[0007] Furthermore, a sludge state determination method according to one aspect of the present invention is a sludge state determination method performed by one or more information processing devices, and includes: a sludge image acquisition step of acquiring an image of aggregated sludge in which a plurality of flocs formed by agglomerating solid suspended matter in the sludge overlap as a sludge image; a first image acquisition step of performing edge processing on the sludge image, then binarization processing, and further closing processing to acquire a first image; and a determination step of determining the state of the aggregated sludge using the first image. [Effects of the Invention]

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

[0009] [Figure 1] This is a block diagram showing an example of the main components of an information processing device according to one embodiment of the present invention. [Figure 2] This figure shows an example configuration of a water treatment system including the above-mentioned information processing device. [Figure 3] This figure shows an example of a sludge image acquired by the sludge image acquisition unit of the above-mentioned information processing device. [Figure 4] This figure shows an example of an image created by various processes in the first image acquisition unit of the above-mentioned information processing device. [Figure 5] This figure shows an example of a second image acquired by the second image acquisition unit of the above-mentioned information processing device. [Figure 6] This figure shows another example of the sludge image, the first image, and the second image acquired by the sludge image acquisition unit, the first image acquisition unit, and the second image acquisition unit, respectively. [Figure 7] This figure shows yet another example of the sludge image, the first image, and the second image acquired by the sludge image acquisition unit, the first image acquisition unit, and the second image acquisition unit, respectively. [Figure 8] This flowchart shows an example of the index value calculation process performed by the above-mentioned information processing device. [Modes for carrying out the invention]

[0010] One embodiment of the present invention will be described below with reference to Figures 1 to 8.

[0011] (Water treatment system) The outline of the water treatment system 100 according to this embodiment will be described with reference to Figure 2. Figure 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 the liquid to be treated into solid suspended matter and liquid, and as shown in Figure 2, it includes an information processing device 1, a control device 3, a flocculator 5, an additive device 6, and a dewatering machine 9. In the following, an example will be described in which the liquid to be treated is sludge produced by biological treatment of sewage, etc. Sludge is a liquid containing solid suspended matter and can also be called slurry.

[0012] The flocculator 5 is a device that coagulates solid suspended matter in sludge to form flocs and obtain coagulated sludge. The flocculator 5 shown in Figure 2 is equipped with a coagulation tank (also called a stirring tank) 51 (tank), a stirring blade 52, a motor 53, and an inspection window 54 (window). The motor 53 rotates the stirring blade 52, which stirs the sludge in the coagulation tank 51, so the flocculator 5 can also be said to be a stirring device. The flocculator 5 is also equipped with a sludge inlet 55, a chemical inlet 56, and a discharge port 57.

[0013] 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 water treatment 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 example in Figure 2. The imaging device 72 may be used to take images from above the liquid surface. Alternatively, the imaging device 72 may be submerged in water for taking images.

[0014] The dewatering machine 9 is installed downstream of the flocculator 5 and is a device that dewaters the flocculated sludge discharged from the flocculator 5. 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. 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.

[0015] In the water treatment system 100, the sludge to be treated 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 according to the sludge processing rate of the flocculator 5 and the dewatering machine 9.

[0016] Then, based on the control of the control device 3, the adding device 6 injects a chemical (including at least a flocculant) for aggregating sludge into the aggregation tank 51 from the chemical injection port 56. In this state, the motor 53 is driven to rotate the stirring blade 52, stirring the sludge and the chemical in the aggregation tank 51 to form flocs. Then, the aggregated sludge, which is a mixture of the formed flocs and the water contained in the sludge, is discharged from the discharge port 57. The chemical may be injected in advance into the sludge before it is introduced into the flocculator 5 from the sludge inlet 55.

[0017] During the process of forming these flocs, the imaging device 72 takes an image. Since this image shows the aggregated sludge including a plurality of flocs and the interstitial water existing in the gaps between the plurality of flocs, it is hereinafter referred to as a sludge image. In the sludge image, a plurality of flocs are shown overlapping, making it difficult to calculate the number of flocs and the area of each individual floc. Therefore, the information processing device 1 detects and analyzes the background area rather than the flocs from the sludge image to calculate an index value indicating the formation state of the flocs.

[0018] Subsequently, this aggregated sludge is supplied into the outer cylinder screen 91 from the sludge inlet 93 of the dehydrator 9. Inside the dehydrator 9, the above-mentioned aggregated sludge is dehydrated under pressure by the screw 92, the filtrate is discharged from the filtrate discharge port 94, and the dehydrated cake after the aggregated sludge is dehydrated is discharged from the dehydrated cake discharge port 95.

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

[0020] As described above, the water treatment system 100 includes an additive device 6 for adding an agent to the sludge in the coagulation tank 51 that coagulates solid suspended matter, a flocculator 5 for stirring the sludge in the coagulation tank 51, an imaging device 72 for photographing the flocs in the coagulation tank 51 through an inspection window 54, an information processing device 1 for calculating an index value indicating the floc formation state from the image captured by the imaging device 72, and a control device 3 for controlling at least one of the amount of agent added by the additive device 6 and the stirring speed according to the calculated index value.

[0021] As described above, the information processing device 1 detects the background area rather than the flocs themselves from the sludge image and calculates an index value indicating the floc formation state by analyzing it. Therefore, it is possible to calculate an index value that accurately indicates the floc formation state from a sludge image in which multiple flocs overlap. As a result, the floc formation state, and consequently the state of the flocculated sludge, can be accurately grasped from the index value. Furthermore, controlling the amount of chemical added and the stirring speed are both effective in changing the size of the flocs. Thus, the water treatment system 100 can automatically improve the floc formation state while treating the sludge and stably generate flocs of an appropriate size.

[0022] (Information processing device) A more detailed description of the information processing device 1 will be given based on Figure 1. Figure 1 is a block diagram showing an example of the main components of the information processing device 1. As shown in Figure 1, 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 (e.g., a control device 3), an input unit 13 that receives input to the information processing device 1, and an output unit 14 for 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 sludge images from the imaging device 72 via the communication unit 12. The sludge image acquisition unit 101 sends the acquired sludge images 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 binarizes it, and then performs closing processing to acquire a first image divided into a flock region and a background region. If the sludge image is a color image, it is desirable that the sludge image be converted to 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 the process of detecting the boundary between bright and dark areas in an image, specifically, the process of detecting areas where the grayscale value (luminance value) changes abruptly. Examples of edge processing include the Sobel filter and the Laplacian filter. Binarization is the process of assigning each pixel in an image to either white or black based on a threshold. For the above binarization process, static binarization may be performed in which the threshold is predetermined, or dynamic binarization may be performed in which a threshold is set for each small region in the image.

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

[0027] The second image acquisition unit 103 binarizes the sludge image from the sludge image acquisition unit 101 to acquire a second image divided into a flock 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 to a grayscale image before being binarized. The sludge image, the first image, and the second image will be described later based on Figures 3 to 5.

[0028] The determination unit 104 uses either the first image from the first image acquisition unit 102 or the second image from the second image acquisition unit 103, or both, to determine the state of the coagulated sludge. 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 result of determining the state of the flocculated sludge. Specifically, the determination unit 104 detects the background region using either or both of the first and second images, and analyzes a plurality of sub-regions constituting the background region to calculate the index value. For example, the determination unit 104 considers a continuous region consisting of adjacent pixels among the pixels included in the background region as one sub-region and counts the number of sub-regions. The determination unit then calculates the index value as the value obtained by dividing the total area of ​​the background region by the number of sub-regions, i.e., the average area of ​​the sub-regions. Details of the index value are described in the aforementioned Patent Document 2, so their explanation is omitted here.

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

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

[0032] (Regarding the sludge images, Image 1, and Image 2) Figure 3 shows an example of a sludge image A1 acquired by the sludge image acquisition unit 101. In the sludge image A1 shown in Figure 3, the floc regions are lighter in color than their background regions, and the pore water present in the gaps between multiple flocs appears cloudy. In addition, the floc regions contain numerous irregularities.

[0033] Figure 4 shows an example of images a10 to a13 created by various processing in the first image acquisition unit 102. Image a10 in Figure 4 is an image obtained by converting the sludge image A1 shown in Figure 3 to a grayscale image and then performing edge processing. In the example in Figure 4, the conversion coefficients to grayscale were R = 299, G = 587, and B = 114. In image a10 in Figure 4, the edge regions are brighter than other regions. Also, the flock regions contain a large number of edge regions.

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

[0035] Image a12, shown in Figure 4, is the image a11 after being processed with a closing process. Compared to image a11, in image a12, the noise has been removed, resulting in more connected edge regions and a wider white area, making it closer to a flocked area.

[0036] Image a13 shown in Figure 4 is an image a12 that has been subjected to an expansion process. Comparing the sludge image A1 shown in Figure 3 with image a13 shown in Figure 4, it can be seen that the floc region in image a13 is almost white. Therefore, image a13 is the first image a1, which is divided into a floc region and a background region.

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

[0038] Referring to the sludge images A1, first image a1 (a13), and second image a2 shown in Figures 3 to 5, it can be seen that in the left side of sludge image A1, the pore water region 300, which shows a white turbidity with a color similar to flocs, becomes a black region 301 in first image a1, while it becomes a white region 302 in second image a2. Therefore, compared to second image a2, first image a1 is an image in which the boundary between pore water and flocs is closer to the actual state of the sludge when white turbidity occurs in the pore water.

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

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

[0041] Incidentally, if the interstitial water is cloudy, it may indicate that the amount of chemical added by the addition device 6 is insufficient. In such cases, 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] Furthermore, in the example shown in Figure 4, the first image acquisition unit 102 performed the edge processing using a Sobel filter. By using a Sobel filter, edges are enhanced while noise is reduced, so the first image a1 can be obtained as being closer to the actual sludge state, and the state of the flocculated sludge can be determined more appropriately.

[0043] Furthermore, in the example shown in Figure 4, the first image acquisition unit 102 performs an expansion process on the closing image a12 to acquire the first image a1 (a13). This makes it possible to obtain the first image a1 in which the flocs and pore water are well separated, allowing for a more appropriate determination of the state of the flocculated sludge.

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

[0045] Referring to Figure 6, it can be seen that the second image b2 shows a boundary between pore water and flocs that is closer to the actual sludge state compared to the first image b1. Furthermore, the index value calculated by the determination unit 104 using the first image b1 was 450 pixels. On the other hand, the index value calculated by the determination unit 104 using the second image b2 was 401 pixels, which is a value closer to the actual floc formation state.

[0046] From this, it can be understood that the determination unit 104 may calculate the index value using the first image if it determines that the pore water is cloudy, while it may calculate the index value using the second image if 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 pore water.

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

[0048] Referring to Figure 7, the floc region 310 on the right side of the sludge image C1 becomes a region 311 that is indistinguishable from the black region in the first image c1, while in the second image c2 it becomes a region 312 that is clearly separated from the black region.

[0049] On the other hand, compared to the pore water region 320 on the left side of sludge image C1, the pore water region 321 in the first image c1 is of a similar size, while the pore water region 322 in the second image c2 is narrower. At this time, the index value calculated by the determination unit 104 using the second image c2 was 632 pixels. On the other hand, the index value calculated by the determination unit 104 using the first image c1 was 779 pixels, which was a value close to the actual floc formation state.

[0050] Thus, even when there is no turbidity in the pore water, the first image c1 may be closer to the actual sludge state in terms of the boundary between the pore water and the flocs compared to the second image c2. In this case, the determination unit 104 can appropriately determine the state of the flocculated sludge by using such a first image c1. Furthermore, since the determination unit 104 obtains an index value indicating the floc formation state by focusing on the background region rather than the flocs, it can accurately grasp the floc formation state and, consequently, the state of the flocculated sludge from the index value.

[0051] (Calculation process for indicator values) The flow of the index value calculation process (sludge state determination method) performed by the information processing device 1 will be explained based on Figure 8. Figure 8 is a flowchart of an example of the index value calculation process performed by the information processing device 1. The processes S1 to S9 described below are performed continuously while the water treatment system 100 is in operation. In addition, while the water treatment system 100 is in operation, the imaging device 72 takes pictures at predetermined intervals, and the captured images are acquired as sludge images by the sludge image acquisition unit 101 of the information processing device 1.

[0052] In S1, the sludge image acquisition unit 101 acquires a sludge image from the imaging 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 binarizes it, and then 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 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 simultaneously with S2.

[0053] In S4, the determination unit 104 detects the background region for both the first and second images, analyzes the multiple sub-regions constituting the background region, and calculates an index value. In S5, the determination unit 104 determines whether the index value calculated using the first image is greater than or equal to a predetermined value compared to 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 a predetermined value greater than the index value calculated using the second image (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 or equal to a predetermined value greater than the index value calculated using the second image (No in S5), the process proceeds to S7.

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

[0056] In S8, the instruction unit 105 determines whether the control device 3 needs to control the equipment based on the index value of the determination result determined by the determination unit 104. Figure 8 illustrates an example where the equipment to be controlled is the motor 53, that is, an example where 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 additive device 6 or other devices.

[0057] If it is determined in S8 that control is not necessary (No in S8), the process shown in Figure 8 ends. On the other hand, if it is determined that control is necessary (Yes in S8), the process proceeds to S9. The criteria for determining whether control is necessary can be predetermined; for example, the indicator unit 105 may determine that control is necessary if 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 floc is stirred per unit time. Specifically, the instruction unit 105 changes the number of stirs by instructing the control device 3 to change the rotation speed of the motor 53, and this completes the process shown in Figure 8. The method for changing the rotation speed has already been explained, so it will not be repeated here.

[0059] [Examples of implementation using software] The function of the information processing device 1 (hereinafter referred to as "the device") is a program that causes the device to function as a computer, and can be realized by a program (sludge state determination program) that causes each control block of the device (particularly each part included in the control unit 10) to function as a computer.

[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., 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.

[0061] 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.

[0062] 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.

[0063] 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).

[0064] 〔summary〕 An information processing apparatus according to embodiment 1 of the present invention includes: a sludge image acquisition unit that acquires a sludge image taken by a camera of agglomerated sludge in which a plurality of flocs formed by agglomerating solid suspended matter in sludge overlap; a first image acquisition unit that performs edge processing on the sludge image, then binarization processing, and further closing processing to acquire a first image; and a determination unit that determines the state of the agglomerated sludge using the first image.

[0065] An information processing device according to aspect 2 of the present invention, in the above-described aspect 1, includes a second image acquisition unit that performs binarization processing on 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 pore water present in the gaps between the plurality of flocs is cloudy.

[0066] In the information processing apparatus according to embodiment 3 of the present invention, in embodiment 2 described above, if the determination unit determines that the pore water is cloudy, it may detect the background region of the floc from the first image and analyze a plurality of sub-regions constituting the background region to calculate an index value indicating the formation state of the floc. On the other hand, if the determination unit determines that the pore water is not cloudy, it may detect the background region of the floc from the second image and analyze a plurality of sub-regions constituting the background region to calculate an index value indicating the formation state of the floc.

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

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

[0069] In the information processing apparatus according to embodiment 6 of the present invention, in embodiments 1 to 5 described above, the first image acquisition unit may perform an expansion process after performing the closing process to acquire the first image.

[0070] In the information processing device according to embodiment 7 of the present invention, in embodiment 2 described above, if the determination unit determines that the interstitial water is cloudy, it may instruct the control device, which controls the amount of chemical added to the liquid to be treated in order 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 additive device for adding a chemical agent for coagulating solid suspended matter to a liquid to be treated in a coagulation tank; an imaging device for photographing the coagulated sludge in the coagulation tank; an information processing device according to aspects 1 to 7 above for determining the state of the coagulated sludge from the image captured by the imaging device; and a control device for controlling the amount of the chemical agent added by the additive device according to the state of the coagulated sludge.

[0072] A sludge state determination method according to aspect 9 of the present invention is a sludge state determination method performed by one or more information processing devices, comprising: a sludge image acquisition step of acquiring an image of aggregated sludge in which a plurality of flocs formed by agglomerating solid suspended matter in the sludge overlap as a sludge image; a first image acquisition step of performing edge processing on the sludge image, then binarization processing, and further closing processing to acquire a first image; and a determination step of determining the state of the aggregated sludge using the first image.

[0073] An information processing device according to any of embodiments 1 to 7 of the present invention may be implemented by a computer. In this case, a sludge state determination program for an information processing device, which is implemented by operating the computer as each part (software element) of the information processing device, and a 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 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]

[0075] 1. Information Processing Device 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 Agitator blades 53 Motor 54 Inspection window 55 Sludge inlet 56 Drug input slot 57 Outlet 71 Lighting equipment 72 Imaging device 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 acquires a sludge image taken by a camera for coagulated sludge in which multiple flocs formed by the aggregation of solid suspended matter in the sludge overlap, In determining the state of the aggregated sludge, in order to reduce the influence of the turbidity of the pore water present in the gaps between the multiple flocs, the first image acquisition unit performs edge processing on the sludge image, then binarization, and further closing processing to acquire a first image. An information processing apparatus comprising a determination unit that determines the state of the aggregated sludge using the first image.

2. A sludge image acquisition unit acquires a sludge image taken by a camera for coagulated sludge in which multiple flocs formed by the aggregation of solid suspended matter in the sludge overlap, A first image acquisition unit performs edge processing on the sludge image, then binarization, and further closing processing to acquire a first image. A determination unit that determines the state of the aggregated sludge using the first image, The system includes a second image acquisition unit that binarizes the sludge image to obtain a second image, The determination unit, Using the second image in addition to the first image, it is determined whether or not the pore water present in the gaps between the multiple flocs is cloudy. If it is determined that the interstitial water is cloudy, the background region of the floc is detected from the first image, and the multiple subregions constituting the background region are analyzed to calculate an index value indicating the formation state of the floc. If it is determined that the interstitial water is not cloudy, the information processing device detects the background region of the floc from the second image and analyzes a plurality of sub-regions constituting the background region to calculate an index value indicating the formation state of the floc.

3. The information processing apparatus according to claim 1, wherein the determination unit detects the background region of the flock from the first image and analyzes a plurality of subregions constituting the background region to calculate an index value indicating the formation state of the flock.

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

5. The information processing apparatus according to claim 1, wherein the first image acquisition unit performs an expansion process after the closing process to acquire the first image.

6. The information processing apparatus according to claim 2, wherein, if the determination unit determines that the interstitial water is cloudy, it instructs a control device, which controls the amount of chemical added to the liquid to be treated in order to coagulate solid suspended matter, to increase the amount of the chemical added.

7. An additive device for adding a chemical agent that coagulates solid suspended matter to the liquid to be treated in the coagulation tank, A camera for photographing the flocculated sludge in the aforementioned flocculation tank, An information processing device according to any one of claims 1 to 6, which determines the state of the aggregated sludge from an image captured by the aforementioned imaging device, A water treatment system comprising a control device that controls the amount of the chemical added by the additive device according to the state of the coagulated sludge.

8. A sludge state determination method performed by one or more information processing devices, A sludge image acquisition step involves obtaining an image of coagulated sludge, which consists of multiple flocs that overlap and are formed by the aggregation of solid suspended matter in the sludge, as a sludge image. In determining the state of the aggregated sludge, in order to reduce the influence of the turbidity of the pore water present in the gaps between the multiple flocs, the sludge image is edge-processed, then binarized, and then closed to obtain a first image in the first image acquisition step. A sludge state determination method comprising a determination step of determining the state of the coagulated sludge using the first image.

9. A sludge state determination method performed by one or more information processing devices, A sludge image acquisition step involves obtaining an image of coagulated sludge, which consists of multiple flocs that overlap and are formed by the aggregation of solid suspended matter in the sludge, as a sludge image. The first image acquisition step involves performing edge processing on the sludge image, then binarization, and further closing processing to obtain a first image. A determination step of determining the state of the coagulated sludge using the first image, The process includes a second image acquisition step of obtaining a second image by binarizing the sludge image, In the determination step, Using the second image in addition to the first image, it is determined whether or not the pore water present in the gaps between the multiple flocs is cloudy. If it is determined that the interstitial water is cloudy, the background region of the floc is detected from the first image, and the multiple subregions constituting the background region are analyzed to calculate an index value indicating the formation state of the floc. A sludge condition determination method, which, if it is determined that the pore water is not cloudy, detects the background region of the floc from the second image and analyzes a plurality of sub-regions constituting the background region to calculate an index value indicating the formation state of the floc.

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

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