JPS61217741A - Recognition of flock formation state for water purification plant - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

[Detailed Description of the Invention] [Field of Application of the Invention] The present invention provides a
The present invention relates to a method for recognizing floc formation status in a water purification plant that measures the particle size and its distribution using image processing technology.

[Background of the invention]

At water treatment plants, the suspended particles in raw water are small in size, so the process is to agglomerate them into flocs, and then let the flocs settle. This rounding and monitoring of flocs in the floc formation pond (mixing pond) is essential.

Conventionally, flocs have been visually monitored several times a day by water treatment plant maintenance managers. Since it relies on visual inspection, the judgment criteria are subjective and qualitative, and the monitoring results have the disadvantage of being difficult to reflect in driving operations.

Furthermore, since the monitoring frequency is discontinuous, countermeasures against agglomeration failures are delayed, which increases troubles.

In contrast, recently industrial television cameras (ITV)
A method has been adopted in which the flocs in the floc formation pond are monitored using However, even in this case, monitoring remains subjective and discontinuous because it relies on human vision.

In order to improve these drawbacks, Japanese Patent Application Laid-Open No. 54-1432
As described in Japanese Patent No. 96, a method has also been proposed in which a photoelectric conversion device is used to output an electrical signal according to the shape of the floc. However, in practical use, there are the following problems.

In order to recognize the state of floc formation online, it is necessary to install a photoelectric conversion device with a watertight structure in the water of the floc formation pond at the water treatment plant.

At this time, the flocs floating in the floc formation pond accumulate on the photoelectric conversion device having a watertight structure, and if the flocs accumulate beyond a certain level, a phenomenon occurs in which the flocs fall down from the watertight mechanism due to their own weight or the influence of the water flow in the floc formation pond. At this time, if a mass of accumulated flocs enters and passes through the floc observation space by the photoelectric conversion device, the image processing device will recognize that a huge floc has been formed, making it impossible to correctly recognize the floc formation situation. In general, since flock formation ponds are constructed open to the atmosphere, foreign matter such as dead leaves and trash thrown into the air by weather phenomena such as strong winds can land on the flock formation pond.

Even if this foreign matter settles in the floc formation pond and enters and passes through the floc observation space by the photoelectric conversion device, the image processing device will recognize that a huge 70 piece has been formed, and the correct floc formation situation will be detected. become unrecognizable. The recognition information on the floc formation status is applied to control of the amount of coagulant injected into the rapid mixing pond, or control of the rotation speed of the 70-speed rotor in the floc formation pond.

In this case, for example, the amount of flocculant injection should be increased because the flocs that are actually formed are small, but it is mistakenly recognized that huge flocs have been formed, so it is mistakenly determined that the amount of flocculant injection should be decreased. As a result, floc formation cannot be achieved properly, resulting in a burden on filtration, etc. in subsequent processes.

[Purpose of the invention]

An object of the present invention is to provide a method for recognizing floc formation status in a water purification plant that can accurately and continuously measure the particle size and distribution of flocs in a floc formation pond (mixing pond).

[Summary of the invention]

A feature of the present invention is that when the area of each floc in a floc formation pond is measured by image processing and the floc formation status is determined by determining the particle size distribution, etc., the area of one 70 floc is measured. K is such that the floc is not recognized as a floc when it is recognized as a predetermined value or more.

[Embodiments of the invention]

FIG. 1 shows an embodiment of the present invention.

In FIG. 1, taken raw water is led to a rapid mixing basin 20 via a landing tank 10. A stirrer 21 is provided in the rapid mixing pond 20. The agitator 21 stirs the flocculant injected from the flocculant injector 22 .

Stirring paddles 31A and 31B are provided in the floc formation pond 30.
, 3 ICs are provided. The stirring paddles are rotationally driven by stirring motors 32A, 32B, and 32C, respectively. Between the stirring paddles 31A, 31B, and 31C, there are 33 rectifying walls with a large number of holes.

It is separated by 33B. The fine flocs flowing from the rapid mixing pond 20 are sequentially stirred in the floc formation pond 30 by stirring paddles 31, 31B, and 31C. As a result, the minute flocs collide and coalesce to become flocs 34. While the flocs 34 pass through the floc formation pond 30, the particle size gradually increases.

The imaging device 100 converts the image of the flock 34 into an electrical signal using an industrial television camera (not shown).

The image processing device 110 performs image processing of the flock 34 based on the electrical signal obtained from the imaging device 100, and calculates the area S of the flock 34.

The flocs 34 formed in the floc formation basin 30 then flow into the settling basin 40 where they are settled and removed. The supernatant water from which the flocs 34 have been removed is injected into the filtration cell 50. In the filtration cell 50, remaining minute flocs that were not removed in the settling tank 40 are filtered out. The supernatant water flowing out of the filtration cell 50 is supplied to consumers through a drainage pond (not shown), a reservoir (not shown), and the like.

FIG. 2 shows detailed configurations of the imaging device 100 and the image processing device 110.

An industrial television camera (I
The TV) 130 uses a close-up lens 131 to enlarge and recognize an image of the flocs 34 in the floc formation pond 30 through an observation window 121 made of a transparent material such as glass. Wiper 12 driven by wiper drive device 123
2 operates periodically to remove dirt from the surface of the observation window 121. A back screen 124 is provided in the round area for recognizing flock groups with high contrast and accuracy.

The screen 124 is connected to the observation window 1 through a back screen fixture 124B fixed to the airtight container 120.
It is installed in front of 21. The back screen 124 is preferably a dark color in order to accurately recognize white flocks with high contrast. Light shielding cover 142
is provided to darken the surroundings and provide illuminance under a certain condition only by the lighting device 140. By providing the light-shielding cover 142, the image of the flock group is not affected by changes in surrounding illuminance. It is more practical to install a plurality of illumination devices 140 and irradiate the flock from multiple directions.

Note that without providing the light shielding cover 142, the lighting controller 141 controls the lighting device 14 according to changes in ambient illuminance.
0 can also be controlled. Baffle board 125A, 125
B is provided in order to suppress the movement of water within the floc formation pond 30 as much as possible and to avoid blocking the illumination. By suppressing the movement of water, images of 70 groups in a flowing state can be recognized with high accuracy.

Flock image information captured by ITVl 30
is the image recognition device 15 via the ITV controller 132.
Sent to 0. The image recognition control device 160 controls the frequency of flock recognition by the image recognition device 150. in general,
The floc formation situation rarely changes rapidly in a short period of time. Therefore, it is sufficient to perform the flock monitoring operation once every UIO minutes or every hour.

A process in which image information of a flock group is subjected to signal processing within the image recognition device 150 will be described below.

FIG. 3(a) shows an image of a group of flocks recognized by I TV 130. Since the flock group is white, the brightness level is high, and since the background back screen 124 is black, the brightness level of the water is low.

Since the flock group is a grayscale image, it is actually flock 3.
The boundary between 4 and the water part is not clear. FIG. 3(a) shows only the outline of the flock group for simplicity.

FIG. 3(b) shows the distribution of brightness levels obtained by scanning the N person' line on the screen of FIG. 3(a). Brightness level is 256
The brightness level is displayed in stages, with the brightness level increasing toward the top of the vertical axis and decreasing toward the bottom. flock 3
4 is white, so the brightness level is higher. 8g3 figure (
In b), the downward valley portion represents 70 pieces.

The brightness distribution shown in FIG. 3(b) is binarized based on the brightness level threshold of the BB' line. A pixel at a luminance level higher than the threshold is set to ``1#1# level''. A pixel at a luminance level lower than the threshold is set to ``0# level.'' FIG. 3(C) shows a signal waveform obtained by binarizing the screen shown in FIG. 3(a) along the Aλ' line.

By subjecting the entire screen of FIG. 3(a) to the aforementioned binarization process, a binarized screen as shown in FIG. 3(d) is obtained. 300 in FIG. 3(d) indicates each pixel. The sum of 300 pixels of each 70 pixels (Ns
t, i=1...n), the area of each floc (S+
, i=1.2. ... n) is calculated using the following formula.

S + = Ct X Nst - (1
) C1:Actual area corresponding to 1 pixel A signal of the calculated area is output from the image recognition device 150.

Through the process described above, the area SL of each floc is measured.

Next, the process of forming flocs will be explained.

At water purification plants, the suspended particles in raw water are small in size, so the process is to agglomerate them into flocs, and then let the flocs settle.

In the rapid mixing pond 20, when a flocculant, which is a positively charged colloid, is injected into raw water suspended fine particles, which are negatively charged colloids, the suspended fine particles are combined with the flocculant. However, when tied together, a micro flock is created. Subsequently, in the flocculation pond 30, the microflocs flow and collide with each other by the rotation of the stirring paddles 31A to 31C of the 70-thculator to form flocs. Now, the flocs in floc formation a30 are flora curators.
As the flocs are more agitated, the frequency of floc-to-flock collisions increases. Collision promotes growth into larger flocs.

On the other hand, for flocs that have grown to a certain size, the agitation by the flocculator acts as a type of shearing force, which has the dual effect of destroying large flocs. For this reason, empirically, the particle size of the flocs formed in the 70-tsuk formation pond is several -
That's about it. This is well known by those skilled in the art. A predetermined area S, which is larger than the area that can be considered to exist as a large floc, is set in the calculation device 210,
The arithmetic unit 210 compares the floc area SL determined by the image processing device 110 with a predetermined set area S. The arithmetic unit 210 recognizes it as a flock when 5t(S), and recognizes it as a foreign object instead of 70 pieces when SL>84.

With the processing described above, it is possible to remove foreign matter and recognize only flocs.

A specific example will be described below using FIGS. 4 to 9.

Note that FIG. 4.6.8 shows the imaging device 10 in FIG.
FIG. 2 is a diagram showing only the parts necessary for explaining 0.

FIG. 4 shows a baffle plate 125A of the imaging device 100.

The lumps 500 of flocs deposited on the board 125B wrinkle due to their own weight or the influence of water flow, etc.

125B is a diagram illustrating a case in which the bird slides down from 125B and enters and passes through the flock observation space 400. FIG. At this time, Fig. 5(a)
Image information as shown in can be obtained. This image information is binarized using a certain brightness level threshold, and the nine values are shown in Figure 5(b).
It is. Each flock in Figure 5(b) is numbered 4.
1.2...5. Next, the area (81 to SS) of each of the flocks A1 to A5 is calculated and compared with a predetermined set area S. In the case of FIG. 5(b), assuming that only the area S3 of 70 pieces of 43 is recognized as being larger than the predetermined set area S, the object &3 is recognized as not being a flock.

FIG. 6 shows an example of a foreign object 501 landing on or entering the floc formation pond 30, and FIG.
) is binarized and numbered as shown in Figure 7(b).
). In the case of FIG. 7(b), the object &4 is recognized as not being a flock.

FIG. 8 shows an example in which the imaging device 100 is provided with a wiper 122 to remove dirt from the surface of the observation window 121. The operation of the wiper 122 and the operation of capturing image information by the ITVI 30 are designed not to overlap. However, when the image information exists on the screen of the wiper 122 due to a malfunction of the wiper 122 or the like and the image information is taken in, the image information becomes as shown in FIG. 9(a). The image information shown in FIG. 9(a) is binarized and numbered. In the case of FIG. 9 Φ), the object &2 is recognized as not a flock.

FIG. 10 shows an example of a processing flow in accordance with the above description.

The image information of the flock 34 is taken in by the ITV 130 in FIG.
50 (step 81).

The image recognition device 150 performs a binarization operation on the flock image information sent to the image recognition device 150 in step S2, and assigns a number (step 83)'f: After passing through the step S
4. Calculate the area SI. In step S5, the calculation device 2
In step 10, the area SL of each flock sent from the image size recognition device fft150 and the set area 8 set in the calculation device 210 are calculated. Perform a comparison with When Sl<8-, the object is recognized as a floc (step S 6 ), and the floc formation status is grasped by calculating L, for example, the particle size distribution (step 87). Further, when SL>S, the object is recognized as a foreign object rather than a floc, and is removed without being included in the information to be processed (step 88), and a warning etc. is output (step 89).

By repeating these steps 81 to 9,
It becomes possible to accurately and continuously recognize the state of floc formation without being affected by foreign objects that have entered or passed through the floc observation space 400 of the imaging device 100.

In addition, by using the particle size distribution obtained in step S7, etc., it is possible to control the amount of coagulant injected, the amount of alkali agent injected, etc., and control the rotational speed of the stirring paddles 31A to 31C.

Next, as shown in FIG. 11(a), the floc formation pond 3
A case will be described in which a part of the foreign object 501 that has landed on water or invaded 0 is obtained as image information in the flock observation space 400.

The image information obtained when the flocs 34 and part of the foreign object 501 are obtained as image information in the floc observation space 400 as shown at 502 in FIG. 11(a) is binarized at a certain brightness level threshold. It is FIG. 11(b). 11th
Number each object in figure Φ) 1.2,3
．． Set it to 4. Although the area 82 of the object A2 in Fig. 11(Φ) is part of the object 501 in Fig. 11(a), it is mistakenly assumed to be the predetermined set area S, or 70 tsu when it is smaller. Recognized. Similarly, although the object &40 area S4 in FIG. 11(b) is part of the flock 502 in FIG. 11(a), it is erroneously recognized as a flock with area S4.

As described above, depending on the timing of capturing the image information, part of the foreign object or part of the 70 pieces may be obtained as image information in the peripheral area of the flock observation space, so there is a possibility that erroneous recognition may occur.

This problem can be solved as follows.

Before numbering the image information t-binarized image information Φ) in FIG. 11(a), the image information shown in FIG. 11(C) is
As shown in the figure, the ``1'' level (same level as the flock) is written on all four peripheral sides of the binarized image quality information with a width of at least one pixel. By doing this, as shown in FIG. 11(C), all objects 501 and 502 whose parts are obtained as image information are connected to the peripheral part of the flock observation space, and are recognized as one object. Ru. Therefore, when numbering is applied to FIG. 11(C), part of the object is obtained as image information in the peripheral area of the flock observation space, and all objects 501 and 502 are recognized as one object 41. Ru. And this object AI
By recognizing objects that are not flocs, it is possible to recognize objects in the floc observation space other than those for which the entire image has been obtained as image information to be outside the scope of understanding the floc formation status, and to accurately It becomes possible to recognize flocs.

〔Effect of the invention〕

As explained above, according to the present invention, it is possible to accurately recognize only flocs without being affected by foreign objects that have entered the floc observation space of the imaging device. can be automatically measured online, objectively, quantitatively, and with high precision. This makes it possible to save labor and improve reliability in water treatment plant maintenance and management, and even to apply it to control systems.

[Brief explanation of the drawing]

FIG. 1 is a configuration diagram showing one embodiment of the present invention, and FIG.
A detailed configuration diagram of the main parts of the figure, Figure 3 is an explanatory diagram of image signal processing,
4 to 9 are detailed explanatory diagrams of the present invention, FIG. 1O is an operation flow diagram, and FIG. 11 is an explanatory diagram of image recognition. 10...Water landing well, 20...Rapid mixing pond, 30...
Flock formation pond, 100...imaging device, 110...
Image processing 72 figures ¥3 figures ¥'/-Figure 75 legs QNσri 76 figures''iJT figures ¥80 /θO ¥9■ ¥10 factors

Claims (1)

[Claims] 1. In a water treatment plant where a flocculant is injected into raw water and then introduced into a flocculation pond to grow flocs, the area of each individual floc in the flocculation pond is measured by image processing, and the area of the measured flocs is A method for recognizing a floc formation situation in a water purification plant, characterized in that when recognizing the floc formation situation from the above, if the area of each individual floc exceeds a predetermined value, the floc is not recognized as a floc.