TWI407089B - Method for monitoring chemical precipitation - Google Patents

Abstract

A method for monitoring chemical precipitation is disclosed, comprising pumping a wastewater into a receiver, irradiating the wastewater in the receiver with a light source, capturing images of the waste water with an image capturing device, and analyzing RGB values of the images to monitor chemical precipitation of the waste water.

Description

Method of monitoring the effectiveness of chemical precipitation

The present invention relates to a monitoring technique for wastewater treatment, and more particularly to a method for monitoring the effectiveness of chemical precipitation.

Water and wastewater treatment consists of many different physical and chemical processes, and chemical precipitation is a very important process in many processes. General wastewater treatment or academic research analyzes the growth of rubber feathers by the following methods: traditional particle size detection and analysis instruments, on-line turbidity meter to judge the growth tendency of rubber feathers in the process of wastewater treatment and photometric dispersion analyzer , hereinafter referred to as PDA). Although the traditional particle size detection and analysis instrument can accurately measure the growth of rubber feathers during wastewater treatment, it has the following restrictions:

(a). The sampling process may damage the rubber feathers and fail to truly reflect the growth of the rubber in the system.

(b) Samples must be diluted to the appropriate concentration by experience or error and can be analyzed.

(c) Although the particle size can be accurately analyzed, the equipment is quite expensive (about 1 to 2 million NT dollars), which is a considerable burden for small processing systems. For coagulation or chemical precipitation, although the particle size information directly reflects the treatment effect, it is not necessarily necessary information, so it is not required for water quality projects in the actual waste water treatment.

(d). When the rubber feather is too heavy and too heavy, it will precipitate in the monitoring tank, so it cannot be measured.

The line turbidity meter can judge the tendency of the rubber feathers to grow during the wastewater treatment process. However, it has the following disadvantages:

(a). The turbidity itself is interfered by the chromaticity. Although the infrared light can be used as the light source to reduce the chromaticity interference, the effect of the chromaticity change during the coagulation process on the scattered solid light scattering signal is reduced, but the chemical precipitation of copper is For example, when gel feathers are formed and precipitated, the chromaticity can also reflect the copper removal efficiency. Therefore, the simple removal of the chroma factor cannot truly judge the effect of chemical precipitation.

(b). Since the scale of the turbidity meter is relatively rough, for example, when the turbidity is 100 NTU, the water sample is quite turbid. Therefore, in the initial stage of the formation of the rubber feather, the turbidity meter has a small range of signal jitter, and it is difficult to observe the optical signal. Variety.

The fiber optic gel feather detector (PDA) uses a curved tube to simulate slow mixing and sends the water sample into the detection device. Although the results show that the simulated slow mixing result is similar to the slow mixing result of the bottle cup test, it is still not true reactive glue. The feather grows in the slow mixing pool. The output map of the fiber optic gelation detector (PDA) is obtained after statistical analysis. The selected parameters (such as time difference) during monitoring will affect the statistical data and affect the interpretation of the coagulation results.

According to the above problems, the industry needs to observe the effect of wastewater treatment in the early stage of rapid mixing and/or slow mixing. This method can not only analyze the effect of wastewater treatment in real time, but also provide images of wastewater treatment, so that factory personnel can directly image Watch the size and structure of the rubber feathers and immediately know the size and distribution of the rubber feathers.

The invention provides a method for monitoring the effect of chemical precipitation, comprising: pumping a waste water into a container; irradiating the waste water in the container with a light source; capturing an image of the waste water by using an image capture device; and analyzing the RGB value in the image To detect the chemical precipitation of wastewater.

The above described objects, features and advantages of the present invention will become more apparent and understood.

According to Beer-Lambert Law, the higher the concentration of suspended particles in water, the weaker the transmitted light intensity, and the more scattering, the more turbid the water. When a solution of suspended solids is irradiated with a light source, if the concentration is relatively low, only a small portion of the image of the water sample is an image of suspended solids, and the rest is a background color such as black. When the concentration is high, many positions in the image are occupied by the suspended solids, so the proportion of the background color of the water sample is lowered, and the color of the particles in the water is visually more and more obvious. If kaolin is taken as an example, when the concentration is high, the water sample will appear white, and the higher the concentration, the more light is scattered, the whiter the water sample is, and the color of the image is related to the concentration, that is, under the difference of the concentration. The level of concentration can be known by the naked eye. If the color of the glue feather image is digitized, the identification of the concentration can be more accurate. On the other hand, if the weight concentration of the particles in the water body is the same, the water sample having a larger average particle diameter has less scattered light due to the smaller number of particles, and visually has fewer white spots in the field of view. Therefore, the color of the water sample is gray.

1 is a view showing a device for monitoring a floc image color analysis system of wastewater according to an embodiment of the present invention, a sedimentation tank 104 in which a stirring device 102 is disposed, and a peristaltic pump 106 can set the sedimentation tank 104. The waste water is pumped into a quartz tube 110. A uniformly uniform light source 108 illuminates the quartz tube 110 containing the wastewater, and at the other end draws an image of the wastewater by a network camera 112, wherein the light source 108 is at an angle of 90 to the network camera 112, and the light source 108 and the net The road camera 112 isolates the external light source interference, and the image is captured by the network camera 112 and transmitted to a data storage and processing device 114 such as a computer to analyze the RGB values in the image due to scattering of suspended particles in the suspension solution.

Fig. 2 is a flow chart showing a method for monitoring the effect of chemical precipitation by image color analysis according to an embodiment of the present invention. In step S201, the image of the wastewater is continuously extracted, and then, in step S202, the image is analyzed, and the RGB value S202 of the image is output. Then, step S203 is performed to analyze and analyze the RGB values, and the image obtained by analyzing the image obtained by the gel feather image color analysis monitoring system and the RGB values obtained at different times can be interpreted as follows:

1. Heavy metal removal efficiency - After calculating the BR difference and the GR difference, the heavy metal removal rate is estimated based on the BR difference and the GR difference.

2. Calculate the falling slope of the RGB value of the slow mixing zone.

3. Calculate the RGB standard deviation value (SD) of the slow mix.

4. Calculate the turbidity value using the relationship based on the RGB values.

[Examples - Heavy Metal Removal Efficiency]

Taking copper simulated wastewater as an example, the optical image monitoring system is used to analyze the color of the rubber feather optical images of different pH and different coagulation doses. Attachment 1 shows the image of the wastewater at different times, and the change in the image size of the rubber feather can be clearly observed from the photograph. Figure 3 shows the change of image RGB during pH adjustment, fast mixing, and slow mixing after adjusting pH and adding coagulant. The pH is 9 and the initial copper concentration is 145~165ppm. Polyaluminium chloride PACl is added. The amount is 0.2 mg/L. Figure 4 shows the change of image RGB during pH adjustment, fast mixing, and slow mixing after adjusting pH and adding coagulant. The pH is 6.5, the initial copper concentration is 145~165ppm, and polyaluminum chloride (PACl). The dosage was 0.4 mg/L. As shown in Fig. 3 and Fig. 4, the RGB value rises sharply after adjusting the pH. This is because the copper ions are mainly dissolved in the solution before the pH is adjusted, and the copper hydroxide precipitate is formed after adjusting the pH. The amount of suspended particles is greatly increased, so the intensity of scattered light rises sharply. After rising, the RGB value decreases due to the accumulation of suspended precipitates. It can be seen from Fig. 3 and Fig. 4 that at high pH, the difference between the B value and the R value is larger. After verification by other different pH values, the R signal is used as a reference to calculate the BR difference (ie, BR) and After the difference of GR (ie, GR), the higher the pH value, the higher the copper removal rate, the higher the BR and GR values. After the regression analysis, the copper removal rate has a very high correlation with the BR and GR values. The correlation is as shown in formula (1).

Copper removal rate = 8.185 (B-R) - 6.01 (G-R) + 27.582 (1)

[Declining slope of RGB value in slow mixing zone]

Comparing the values of the signals after the 3rd and 4th (slow-mix) signals, we can see that the trend of the RGB signal drop in Figure 4 is more obvious. This is because the glue feathers in Figure 4 are effectively coagulated, making the water sample The whole begins to show a clearer image. Compared with other different dosages, it is found that the better the gel length is, the lower the slope of the RGB signal in the fast mixing zone is (see Table 1). Therefore, the RGB falling slope can be used to determine the effect of the chemical precipitation.

[Slow mixing RGB standard deviation value]

Taking the image of Annex 1 as an example, the standard deviation (standard deviation, hereinafter referred to as SD) of the RGB signals in the chemical precipitation zone, ie, the initial stage of pH adjustment and the late adjustment, fast mixing and slow mixing zone, can be obtained. The SD value, see Figure 5, Figure 5 can be seen that when the pH is adjusted, the SD rises sharply. From Annex I, it can be seen that the rubber feather size is the largest, and then the rubber feather in the figure is gradually smaller, and the SD value is also It will fall. The system can directly watch the change of the size of the rubber feather, and can use the calculation of the standard deviation to understand the change of the size of the rubber feather in the system.

[Calculation of turbidity value]

Under different water conditions, the turbidity value can be found in the RGB correlation. For example, the pH is 6.5, 7 and 9, and the coagulant dosage is 0.2 mg/L. pH=6.5 turbidity=-1.754B+2.925R+6.191 R ² =0.9685pH=7 turbidity=4.785R -3.677B+71.093 R ² =0.9959pH=9 turbidity = 2.906R-0.878B-82.958 R ² =0.9805R ² High correlation means that the above relationship is highly accurate.

Therefore, after the gel color image analysis is used to establish a database of turbidity and operating conditions for the chemical precipitation system to be monitored, the relationship can be used to continuously calculate the turbidity value of the processing system.

According to the above, the method for monitoring the chemical precipitation effect of the color analysis of the rubber feather image of the present invention can know the effect of the chemical precipitation in the early stage of rapid mixing or slow mixing of chemical precipitation, and can directly understand the rubber feather in the wastewater according to the image of the extracted wastewater. The size of the chemical precipitation is monitored.

Although the present invention has been disclosed in its preferred embodiments, it is not intended to limit the invention, and the invention may be modified and modified without departing from the spirit and scope of the invention. The scope of protection is subject to the definition of the scope of the patent application attached.

102. . . Stirring device

104. . . Sedimentation tank

106. . . Pump

108. . . light source

110. . . Quartz tube

112. . . camera

114. . . Data storage and processing equipment

1 is a view showing a device for monitoring an optical image monitoring system for wastewater according to an embodiment of the present invention.

Fig. 2 is a flow chart showing a method for monitoring the effect of chemical precipitation by image color analysis according to an embodiment of the present invention.

Figure 3 is a graph showing the RGB variation of an exemplary wastewater treatment of the present invention.

Fig. 4 is a graph showing the RGB variation of the wastewater treatment of another example of the present invention.

Figure 5 shows a graph of RGB standard deviation values.

Annex I shows wastewater images at different times.

Claims (9)

A method for monitoring the effect of chemical precipitation, comprising: pumping a waste water into a container; illuminating the waste water in the container with a light source; capturing an image of the waste water by an image capture device; and analyzing the RGB value of the image To detect the chemical precipitation effect of the wastewater, wherein the step of analyzing the RGB values in the image comprises calculating a BR difference value and a GR difference value, and estimating a heavy metal removal rate of the wastewater according to the BR difference value and the GR difference value. The method of monitoring the effect of chemical precipitation as described in claim 1, wherein the step of analyzing the RGB values in the image comprises calculating a decreasing slope of the RGB values. The method for monitoring the effect of chemical precipitation as described in claim 2, wherein the decreasing slope of the RGB value is greater, and the effect of the chemical precipitation is better. The method for monitoring the effect of chemical precipitation as described in claim 1, wherein the step of analyzing the RGB values in the image comprises calculating a standard deviation value of the RGB values to obtain a change in the size of the rubber feathers in the wastewater. The method of monitoring the effect of chemical precipitation as described in claim 1, wherein the step of analyzing the RGB values in the image comprises calculating a turbidity value based on the RGB values. The method for monitoring the effect of chemical precipitation as described in claim 1 of the patent application analyzes the RGB values in the image by a computer. The method of monitoring the effect of chemical precipitation as described in claim 1, wherein the image capturing device is a camera. The method of monitoring the effect of chemical precipitation as described in claim 7 of the patent application, wherein the camera is a web camera. For example, the method for monitoring the chemical precipitation effect described in the first paragraph of the patent application can directly understand the size of the rubber feather in the wastewater according to the image of the wastewater, and monitor the chemical precipitation effect.