Nanobubble-containing water evaluation device

Abstract

To provide a nanobubble-containing water evaluation device capable of evaluating the size of nanobubbles in nanobubble-containing water.SOLUTION: A nanobubble-containing water evaluation device comprising a container (11) for storing nanobubble-containing water, an irradiator (12) for irradiating the container (11) with laser light to form an optical path (L) in the nanobubble-containing water, an image sensor (13) for capturing an image of the optical path (L) to generate image data, and an analyzer (14) for determining nanobubbles in the nanobubble-containing water using the image data, the analyzer (14) generates, from the image data, frequency data of a luminance value of scattered light of the laser light generated by the nanobubbles or frequency data of an emission area of the scattered light, and evaluates the size of the nanobubbles in the nanobubble-containing water.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an apparatus for evaluating nanobubble-containing water that is capable of evaluating not only the concentration of nanobubbles in nanobubble-containing water but also the size of the nanobubbles. [Background technology]

[0002] Nanobubble-containing water, which is water containing so-called nanobubbles, is known to have a high cleaning effect. Therefore, various production devices have been proposed, such as devices that can produce nanobubble-containing water more easily or devices that can produce nanobubble-containing water with higher functionality.

[0003] Here, nanobubbles are bubbles with a diameter of less than 1 μm, and are usually recognized as bubbles with a diameter of about 10 to 500 nm. Because of their small size, nanobubbles have little buoyancy, and can remain suspended in water for several weeks to several months.

[0004] It is also known that the size and amount of nanobubbles contained in nanobubble-containing water are important when focusing on its cleaning effect. Therefore, it is necessary to confirm the amount of nanobubbles contained in the produced nanobubble-containing water.

[0005] As a method for confirming the presence of nanobubbles in nanobubble-containing water, a method has been proposed in which the nanobubble-containing water is photographed with a digital camera or the like to generate image data that makes the nanobubbles visible in the nanobubble-containing water, and the nanobubbles are counted using this image data (see, for example, Patent Document 1).

[0006] Another method proposed for confirmation involves irradiating nanobubble-containing water with laser light, causing the nanobubbles in the nanobubble-containing water to diffract or scatter the laser light, and then measuring the intensity of this diffracted or scattered light (see, for example, Patent Documents 2 and 3).

[0007] However, while the method of counting nanobubbles using image data can be applied to so-called microbubbles, it is extremely difficult to photograph nanobubbles at a size that is visible, making it impractical. Furthermore, the method of evaluation using the intensity of diffracted or scattered light generated by laser light requires a high level of precision in the device itself in order to perform stable measurements, which makes the device extremely expensive and often makes it difficult to use casually.

[0008] In view of these circumstances, a method has been proposed that utilizes the Tyndall phenomenon that occurs when nanobubble-containing water is irradiated with laser light as a simpler method for confirming the presence of nanobubbles in nanobubble-containing water. That is, this method utilizes the brightness of scattered light that occurs as a result of the Tyndall phenomenon (see, for example, Patent Document 4).

[0009] Specifically, by irradiating nanobubble-containing water with a predetermined laser beam, the nanobubbles in the nanobubble-containing water scatter the laser beam, causing the Tyndall effect. This Tyndall effect creates a visible light path in the nanobubble-containing water, and image data is generated by photographing this light path with a digital camera. This image data can be used to evaluate the concentration of nanobubbles in the nanobubble-containing water from the average brightness value or average RGB values ​​of the light path. Evaluating the concentration of nanobubbles in nanobubble-containing water through image analysis of the image data provides a relatively inexpensive method for confirming nanobubbles. [Prior art documents] [Patent documents]

[0010] [Patent Document 1] Japanese Patent Application Laid-Open No. 2011-247748 [Patent Document 2] Japanese Patent Application Laid-Open No. 2007-263876 [Patent Document 3] Japanese Patent Application Publication No. 2017-211213 [Patent Document 4] Japanese Patent Application Publication No. 2023-030579 Summary of the Invention [Problem to be solved by the invention]

[0011] However, although it is possible to estimate the concentration of nanobubbles in nanobubble-containing water from the average brightness value or average RGB value using the Tyndall phenomenon described above, it does not guarantee whether the nanobubbles contained in the water are large enough to produce the desired cleaning effect.

[0012] The present inventors have an object to provide a nanobubble-containing water evaluation device that can also evaluate the size of nanobubbles in nanobubble-containing water. [Means for solving the problem]

[0013] The nanobubble-containing water evaluation device of the present invention is provided with a container for storing nanobubble-containing water, an irradiator for irradiating the container with laser light to create a light path in the nanobubble-containing water, an image sensor for generating image data by photographing the light path, and an analyzer for identifying nanobubbles in the nanobubble-containing water using the image data. In particular, the analyzer generates, from the image data, frequency data on the brightness value of scattered light of the laser light generated by the nanobubbles or frequency data on the emission area of ​​the scattered light, and evaluates the size of the nanobubbles in the nanobubble-containing water.

[0014] Furthermore, the nanobubble-containing water evaluation device of the present invention has the following features. (1) The laser light is emitted from a light source that emits a first light, which is one of the three primary colors of light, and the analyzer evaluates the image data based on a second light that is different from the first light. (2) The analyzer determines errors using a third light different from the first light and the second light. [Effects of the Invention]

[0015] According to the present invention, frequency data on the brightness values ​​of scattered light of laser light caused by nanobubbles in nanobubble-containing water or frequency data on the emission area of ​​scattered light is generated from image data, and the concentration of nanobubbles in nanobubble-containing water is evaluated using this data, thereby making it possible to evaluate the concentration while taking into account the size of the nanobubbles. [Brief explanation of the drawings]

[0016] [Figure 1] FIG. 1 is a schematic explanatory diagram of the configuration of an apparatus for evaluating nanobubble-containing water according to the present invention. [Figure 2] FIG. 1 is an explanatory diagram of an apparatus for evaluating nanobubble-containing water according to the present invention. [Figure 3] 1 is a flowchart illustrating the operation of the nanobubble-containing water evaluation device according to the present invention. [Figure 4] FIG. 10 is a reference diagram of image data generated by an imaging element. [Figure 5] FIG. 10 is a reference diagram of luminance distribution data generated from secondary image data. [Figure 6] FIG. 10 is an explanatory diagram of a method for setting a threshold value. [Figure 7] FIG. 10 is a reference diagram of frequency distribution data of luminance values. [Figure 8] FIG. 10 is a reference diagram of frequency distribution data of luminescent area. [Figure 9] 10 is a graph showing the correlation between the average brightness value of the first frequency data and the particle diameter. [Figure 10] 10 is a graph showing the correlation between the average area of ​​the second frequency data and the particle size. [Figure 11] 10 is a graph showing the correlation between the average brightness value of the first frequency data and the concentration of standard particles. DETAILED DESCRIPTION OF THE INVENTION

[0017] As shown schematically in FIG. 1, the nanobubble-containing water evaluation device of the present invention includes a container 11 for storing nanobubble-containing water, an irradiator 12 for irradiating the container 11 with laser light to generate an optical path L in the nanobubble-containing water, an image sensor 13 for capturing an image of the optical path L to generate image data, and an analyzer 14 for identifying nanobubbles in the nanobubble-containing water using the image data.

[0018] Here, the nanobubble-containing water is prepared using an appropriate nanobubble generator. In the nanobubble generator, for example, an air bubble generator having a large number of fine holes is immersed in water, and air bubbles are generated by the air bubble generator, thereby generating the nanobubble-containing water.

[0019] The container 11 is preferably a prismatic quartz cell that is also used in spectrophotometers, etc. The container 11 may also be a beaker, etc.

[0020] The irradiator 12 is preferably a laser light source capable of irradiating laser light of a predetermined single wavelength. This laser light source may be provided with three primary colors, i.e., a red laser light source, a green laser light source, and a blue laser light source, and may be switchable as appropriate. Alternatively, to reduce costs, a laser light source for one color may be used, for example, a green laser pointer may be used as the laser light source. In the following description, unless otherwise specified, it will be assumed that a green laser light source is used.

[0021] The laser light emitted from the irradiator 12 passes through a cylindrical lens 15 and becomes a diffused light whose irradiation area widens as it advances in the irradiation direction.

[0022] When the nanobubble-containing water in the container 11 is irradiated with laser light, the Tyndall phenomenon occurs in which the laser light is scattered by the nanobubbles in the nanobubble-containing water, and the irradiated area of ​​the laser light appears as a visible light path L.

[0023] The imaging element 13 is provided facing a direction perpendicular to the direction in which the optical path L extends.

[0024] The imaging element 13 is configured by a so-called CCD (Charge Coupled Device) image sensor or a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, and is combined with an appropriate lens or the like to capture an image of the light path L as described below, thereby generating image data. A digital camera with a built-in CCD image sensor or CMOS image sensor may also be used.

[0025] The analyzer 14 is a personal computer or the like, and in this embodiment, a tablet-type personal computer is used. A desired program is installed in the storage device of this analyzer 14, and the program is executed by the CPU of the analyzer 14, causing the analyzer 14 to function as a luminance distribution data generating means m1, a nanobubble identifying means m2, a first frequency data generating means m3, a light-emitting area measuring means m4, a second frequency data generating means m5, an evaluation means m6, and an error detecting means m7, as will be described later.

[0026] The analyzer 14 also controls the illuminator 12 and the image sensor 13, and in particular causes image data created by the image sensor 13 to be sequentially input to the analyzer 14. The illuminator 12 and the analyzer 14 are connected by a first wiring 17 via a connector 16 connected to the analyzer 14, and the image sensor 13 and the analyzer 14 are also connected by a second wiring 18 via the connector 16 connected to the analyzer 14.

[0027] It is desirable to place the container 11, the irradiator 12, the cylindrical lens 15, and the image sensor 13 at least in a darkroom. In this embodiment, as shown in FIG. 2, the nanobubble-containing water evaluation device realizes a darkroom state by using a predetermined housing 21.

[0028] The housing 21 of this embodiment has an openable / closable lid 22 on the top surface, and the openable / closable lid 22 can be flipped up to house the container 11 made of a quartz cell inside the housing 21. After the container 11 is housed in the housing 21, the openable / closable lid 22 is closed, thereby creating a darkroom inside the housing 21. The irradiator 12, cylindrical lens 15, and image pickup element 13 are fixedly mounted at predetermined positions inside the housing 21. In addition, the analyzer 14, which is configured as a tablet-type personal computer, is mounted on the top surface of the housing 21 and also functions as an operation panel for the nanobubble-containing water evaluation device.

[0029] The operation of the evaluation system using the nanobubble-containing water evaluation device will be described below based on the flowchart in Figure 3. For convenience of explanation, unless otherwise specified, the description will be given assuming that the irradiator 12 uses a green laser light source.

[0030] First, the main power supply of the nanobubble-containing water evaluation device is turned on (step S1), the operation panel is set to the start-up state, and the calibration mode is selected (step S2). At this time, the irradiator 12 and the image sensor 13 are each in the power-on state, and after completing the initial operation, they are in the idling state.

[0031] In the calibration mode, standard water is placed in a container 11 made of a quartz cell, and the measurement mode operation described below is performed on the standard water to perform initial calibration (step S3). The standard water is prepared by dispersing standard particles in degassed pure water to a predetermined concentration. In this embodiment, the standard particles are particles made of polystyrene resin. For example, commercially available 100 nm standard particles are homogeneous particles with a particle size of 101 nm ± 3 nm. It is desirable to use standard particles with a size similar to the nanobubbles to be contained in the nanobubble-containing water to be evaluated as the standard water. It is also desirable to set the concentration of the standard particles in the standard water to a concentration similar to the concentration expected in the nanobubble-containing water to be evaluated. Not only one type of standard water, but multiple types with different standard particle sizes and concentrations may be used.

[0032] After the calibration mode in step S3 is completed, the measurement mode is selected on the operation panel of the nanobubble-containing water evaluation device (step S4), and a measurement sample is set in the nanobubble-containing water evaluation device.

[0033] In setting the measurement sample, nanobubble-containing water is placed in container 11 made of a quartz cell, water and fingerprints adhering to the surface of container 11 are carefully wiped off, and container 11 is placed in housing 21 of the nanobubble-containing-water evaluation device, and opening / closing lid 22 is closed (step S5). The opening and closing operation of opening / closing lid 22 is detected by a limit switch (not shown), and when it detects that opening / closing lid 22 is closed, irradiator 12 automatically starts irradiating laser light (step S6).

[0034] After the irradiation of the laser light by the irradiator 12, the image sensor 13 captures an image of the light path L and generates image data (step S7). In this embodiment, the image sensor 13 captures an image of a 7.5 x 5.0 mm shooting range and generates image data. Fig. 4 shows a reference example of the image data.

[0035] The image data generated by the image sensor 13 is sequentially output and input to the analyzer 14. Alternatively, the image sensor 13 may capture an image based on a shutter signal input from the analyzer 14, generate image data, and input it to the analyzer 14. The analyzer 14 stores the input image data in memory as primary image data, and then causes the analyzer 14 to function as a trimming means to generate secondary image data by cutting out a portion of the optical path L from the primary image data (step S8). In this embodiment, the secondary image data is image data of 2000 × 200 pixels. It is desirable to generate the secondary image data by cutting out as much of the central portion of the captured optical path L as possible.

[0036] The analyzer 14 executes a luminance distribution data generation program to function as luminance distribution data generation means m1, and generates the luminance distribution data shown in Fig. 5 from the secondary image data (step S9). Specifically, the luminance of gray, which is total scattered light, is calculated at a predetermined gradation from the secondary image data, which is color image data, to obtain the luminance distribution data. In this embodiment, each luminance is calculated at an 8-bit gradation (0-255), but this is not limited to 8-bit gradation.

[0037] Next, the analyzer 14 functions as the nanobubble identifying means m2 by executing a nanobubble identifying program, and identifies individual nanobubbles from the brightness distribution data (step S10).

[0038] In this embodiment, a threshold value is set when identifying nanobubbles. That is, nanobubbles are considered to exist at the top of a mountain-like protrusion that protrudes upward in the brightness distribution data, and this top is called a "peak." In detecting these peaks, a threshold value is set, making it possible to detect individual peaks.

[0039] Explaining this with reference to Figure 6, Figure 6(a) shows one two-dimensional data portion of the three-dimensional luminance distribution data. In this case, the luminance distribution data appears as a first curve C1, in which the luminance value changes continuously along the horizontal axis.

[0040] When the threshold value is set below the first curve C1 as shown in Figure 6(a), the detection program for detecting the peak of this first curve C1 scans from the left end to the right end of the horizontal axis to identify the maximum brightness value, but only one is identified, as shown by the circle in Figure 6(a). Clearly, the peak cannot be detected.

[0041] Next, the threshold is increased by one step as shown in Fig. 6(b). The first curve C1 in Fig. 6(a) intersects with the line at the threshold, and by treating the area below the threshold as not existing, the luminance distribution data in Fig. 6(b) is composed of the second curve C2, the third curve C3, and the fourth curve C4.

[0042] In a detection program that detects peaks for the second curve C2, the third curve C3, and the fourth curve C4, when scanning from the left end to the right end of the horizontal axis to identify the maximum brightness value, the program can distinguish and recognize each of the curves C2, C3, and C4, and can identify the maximum brightness value for each of the curves C2, C3, and C4, thereby identifying the three peaks indicated by circles in Figure 6(b).

[0043] In this way, by raising the threshold value, the peak detection program scans from the left end to the right end of the horizontal axis to identify the maximum brightness value for the fifth curve C5, sixth curve C6, seventh curve C7, and eighth curve C8 in Figure 6(c), the ninth curve C9, tenth curve C10, eleventh curve C11, twelfth curve C12, and thirteenth curve C13 in Figure 6(d), the fourteenth curve C14, fifteenth curve C15, sixteenth curve C16, and seventeenth curve C17 in Figure 6(e), and the eighteenth curve C18, nineteenth curve C19, and twentieth curve C20 in Figure 6(f), thereby identifying the peaks indicated by circles.

[0044] As the number of detected peaks differs depending on the threshold value, in this embodiment, the threshold value is increased in order from the smallest brightness value, and the threshold value at which the maximum number of detected peaks is set as the true threshold value. In Fig. 6, the threshold value shown in Fig. 6(d) is the true threshold value.

[0045] Using the threshold value set in this way, the analyzer 14 identifies the coordinates where the brightness value peaks and the magnitude of the peak, i.e., the brightness value, and determines that nanobubbles exist at the position of this peak.

[0046] After identifying the individual nanobubbles in step S10, the analyzer 14 executes a first frequency data generation program to function as first frequency data generation means m3, and generates frequency data of brightness values ​​with the magnitude of the brightness value on the horizontal axis (step S11), as shown in Fig. 7. The generated frequency data is stored in the memory of the analyzer 14 as appropriate.

[0047] Next, the analyzer 14 functions as a light emission area measuring means m4 by executing the light emission area measuring program, and measures the light emission area of ​​the scattered light of the laser light that is scattered by the nanobubbles (step S12).

[0048] Here, the emission area of ​​scattered light refers to the area of ​​the base of the mountain-shaped peak when a peak is formed, as shown in FIG. 5. In this embodiment, the mountain-shaped peak when a peak is formed is considered to be conical, and the area of ​​the base is evaluated as the number of pixels occupied by the base. However, since it can be difficult to precisely identify the area of ​​the base where the brightness value is "0," this embodiment evaluates the area at a brightness value that is 10% of the peak brightness value. Specifically, in the two-dimensional data portion used to identify the peak described above, two coordinates at a specific peak where the brightness value is 10% of the peak brightness value are identified, and the emission area is the area of ​​a circle whose diameter is the length between these two coordinates. Therefore, the emission area may also be evaluated as the length between the two coordinates described above. The peak coordinate is assumed to exist between the two coordinates described above.

[0049] After measuring the light-emitting area of ​​each nanobubble in step S10, the analyzer 14 executes a second frequency data generation program to function as second frequency data generation means m5, and generates frequency data of the light-emitting area with the size of the light-emitting area on the horizontal axis (step S13), as shown in Fig. 8. The generated frequency data is stored in the memory of the analyzer 14 as appropriate.

[0050] After generating the second frequency data in step S13, the analyzer 14 functions as an evaluation means m6 by executing the nanobubble water evaluation program, and identifies the size and concentration of nanobubbles contained in the nanobubble-containing water of the test subject using the first frequency data or the second frequency data (step S14).

[0051] In this embodiment, the size and concentration of nanobubbles contained in nanobubble-containing water are specifically specified as follows.

[0052] First, in the nanobubble-containing water evaluation device, frequency data corresponding to the first frequency data and the second frequency data is obtained in advance using the standard water described above, and the frequency data is stored as reference data in the memory of the analyzer 14. Here, in this embodiment, the standard water is a dispersion water in which polystyrene resin particles are dispersed in pure water, and multiple types of polystyrene resin particles with different particle sizes are used to create multiple types of standard water with different particle concentrations, and the reference data is generated.

[0053] The first frequency data can be characterized by using this first frequency data to identify the average luminance value, and similarly the second frequency data can be characterized by using this second frequency data to identify the average area.

[0054] Specifically, by specifying the average brightness value (average peak brightness value) of the first frequency data using standard particles with average particle sizes of 300 nm, 500 nm, and 800 nm, the graph showing the correlation shown in Figure 9 can be obtained. Similarly, by specifying the average area of ​​the second frequency data, the graph showing the correlation shown in Figure 10 can be obtained. Note that the particle concentration of each standard water is approximately 1.7 x 10 7 The nanobubble size is set to about particles / ml. By using Figures 9 and 10 as calibration curves, it is possible to determine the size of nanobubbles from the first frequency data or the second frequency data. Note that Figures 9 and 10 are based on currently known data, and it is desirable to use more optimized frequency data for each as the reference data.

[0055] Similarly, by generating reference data for different concentrations of standard particles, as shown in Fig. 11, it is possible to determine the concentration of nanobubbles from the first frequency data or the second frequency data. Fig. 11 is a graph showing the correlation between the average brightness values ​​of the first frequency data for standard water using standard particles with an average particle size of 100 nm and different concentrations of the standard particles. A graph showing a similar correlation can also be obtained when the average area of ​​the second frequency data is used.

[0056] The analyzer 14 may not only identify the size and concentration of nanobubbles using the graphs shown in Figures 9-11 as calibration curves, but may also evaluate the size and concentration of nanobubbles by taking into account the shapes of the graphs of the first frequency data and the second frequency data.

[0057] After evaluating the size and concentration of the nanobubbles contained in the nanobubble-containing water in step S14, the analyzer 14 displays the size and concentration of the nanobubbles as the evaluation results on the display screen (step S15).

[0058] In this way, the nanobubble-containing water evaluation device evaluates the size of the nanobubbles contained in the nanobubble-containing water.

[0059] In the above-described embodiment, the luminance of gray is used when generating the luminance distribution data in step S9, but the luminance of any one of the three primary colors of light may also be used.

[0060] For ease of explanation, in this embodiment, the illuminator 12 is a green laser light source, so the first of the three primary colors of light will be described as "green," the second as "red," and the third as "blue."

[0061] When a green laser light source is used, the light components contained in the optical path L created by irradiating the nanobubble-containing water with laser light contain a large amount of green components, resulting in an increase in the brightness of the green scattered light.

[0062] In such cases, evaluating the luminance of the secondary image data using the red light component allows the luminance to be evaluated without being affected by the light source, resulting in a more accurate evaluation of the luminance value. That is, the secondary image data is irradiated from a light source that irradiates a first light, which is one of the three primary colors of light, and the analyzer 14 evaluates the secondary image data based on a second light different from the first light, thereby enabling a more accurate evaluation of the luminance value. Note that, although a blue light component may be used instead of the red light component, the red light component is preferable because the red light component tends to have a larger luminance value.

[0063] Furthermore, if impurities are mixed into the nanobubble-containing water, the brightness value of even the blue light component tends to be large. Therefore, by evaluating the brightness of the secondary image data using the blue light component, errors caused by impurities can be detected.

[0064] Specifically, in step S9, the analyzer 14 executes a luminance distribution data generation program to function as luminance distribution data generation means m1, and when the analyzer 14 generates the luminance distribution data shown in FIG. 5 from the secondary image data, the analyzer 14 executes an error detection program to function as error detection means m7, and performs error detection.

[0065] That is, when generating the luminance distribution data, the luminance distribution data of the blue light component is generated, and the nanobubble identification means m2 in step S10 functions as an error detection means, thereby enabling the error position to be identified.

[0066] Using this error position information, the first frequency data generating means m3 in step S11 can eliminate the luminance value in the error position information as an error, thereby improving the accuracy of the frequency data of the luminance value.

[0067] In addition, if the nanobubble-containing water evaluation device is equipped with not only a green laser light source but also a red laser light source and a blue laser light source as the irradiator 12, the color of light used for error detection may be selected according to the color of the light source used to generate the optical path L.

[0068] In particular, the present invention utilizes scattered light due to the Tyndall effect, and Mie scattering, which is the cause of the Tyndall effect, reaches its maximum when the wavelength of light is equal to the particle diameter. Therefore, if the size of the nanobubbles in the nanobubble-containing water to be examined is estimated in advance, it is desirable to select the color of the laser light source according to the size of the nanobubbles. [Explanation of symbols]

[0069] 11 Container 12 Irradiator 13 Image sensor 14 Analyzer 15 Cylindrical Lens 16 connectors 17 1st wiring 18 2nd wiring 21 Housing 22 Opening and closing lid L optical path m1 Luminance distribution data generation means m2 Nanobubble identification method m3 First frequency data generation means m4 Luminous area measurement means m5 Second frequency data generation means m6 evaluation method m7 Error detection method

Claims

1. A container for storing nanobubble-containing water; an irradiator that irradiates the container with laser light to create an optical path in the nanobubble-containing water; an imaging element that captures an image of the optical path to generate image data; an analyzer that identifies nanobubbles in the nanobubble-containing water using the image data; A nanobubble-containing water evaluation device comprising: The analyzer generates frequency data on the brightness values ​​of the scattered light of the laser light generated by the nanobubbles or frequency data on the emission area of ​​the scattered light from the image data, thereby evaluating the size of the nanobubbles in the nanobubble-containing water.

2. the laser light is emitted from a light source that emits first light, which is one of the three primary colors of light; The nanobubble-containing water evaluation device according to claim 1 , wherein the analyzer evaluates the image data based on a second light different from the first light.

3. The nanobubble-containing water evaluation device according to claim 2 , wherein the analyzer performs error determination using a third light different from the first light and the second light.

Images