Device and method for detecting chlorophyll concentration of water body

Abstract

The invention relates to a water chlorophyll concentration detection device and method. The water chlorophyll concentration detection device comprises a support, a buoyancy device is arranged on one side of the support, and a laser and a camera are arranged on the other side of the support; the system further comprises a control terminal, the control terminal controls the laser and the camera to be turned on and turned off to collect a fluorescence image of the water body under laser irradiation to obtain a to-be-detected fluorescence image, and then the channel image brightness of the to-be-detected fluorescence image in different color channels is obtained through analysis. And calculating the chlorophyll concentration of the current water body based on the brightness of the channel image. The device has the advantages of being simple in structure, easy to operate, low in cost, wide in monitoring range, real-time and the like, a new method is provided for measuring water quality and water ecosystem health, and the device can be widely applied to the fields of environment monitoring, water resource management, water ecology research and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of chlorophyll monitoring and analysis, and in particular to a device and method for detecting chlorophyll concentration in water. Background Art

[0002] The chlorophyll content in water is an important indicator of water quality and the health of aquatic ecosystems. Traditional methods for measuring chlorophyll in water mainly rely on laboratory analysis, such as high-performance liquid chromatography and spectral analysis. Although these methods are accurate, they have disadvantages such as complex operation, long time consumption, and strong sample destructiveness, and are not suitable for large-scale, real-time on-site monitoring.

[0003] In recent years, non-destructive methods for detecting chlorophyll in water bodies have gradually attracted attention. Among them, laser-induced fluorescence (LIF) technology has become a hot topic of research due to its advantages such as high sensitivity, strong selectivity, and the ability to achieve real-time detection. LIF technology uses laser as an excitation light source to excite chlorophyll molecules in water bodies to fluoresce. By measuring the fluorescence intensity and wavelength distribution, the chlorophyll content can be inferred. Most of the existing laser fluorescence water chlorophyll detection devices use spectrometers, fluorescence spectrometers or portable optical sensors to collect and analyze fluorescence signals. These devices are usually expensive, complicated to operate, have a long response time, and a small monitoring range. Therefore, a device and method are needed to solve the problems of high cost, complicated operation, small monitoring range, and low efficiency of the existing technology. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a device and method for detecting chlorophyll concentration in water, which can solve the problems of high cost, complex operation, small monitoring range and low efficiency in the prior art.

[0005] The technical solution adopted by the present invention to solve its technical problems is: to provide a water body chlorophyll concentration detection device, including: a bracket, a buoyancy device is arranged on one side of the bracket, and a laser and a camera are arranged on the other side; and also includes a control terminal, the control terminal controls the laser and the camera to turn on and off to collect the fluorescent image of the water body under laser irradiation to obtain the fluorescent image to be tested, and then analyzes and obtains the channel image brightness of the fluorescent image to be tested in different color channels, and calculates the chlorophyll concentration of the current water body based on the channel image brightness.

[0006] Furthermore, the laser is used to emit violet light with a central wavelength of 440 nm.

[0007] Furthermore, the laser and the camera are respectively placed at two ends of the bracket, and the relative distance between the two is set so that the bracket can maintain balance when floating.

[0008] Furthermore, the camera is connected to the bracket via a hinge, and the shooting area is adjusted via the hinge.

[0009] The present invention also provides a water body chlorophyll concentration detection device, which is applied to the detection device as described above, and comprises the following steps:

[0010] Acquire the fluorescence image of the water body to be tested under laser irradiation;

[0011] The channel image brightness of the fluorescent image to be tested in different color channels is analyzed, and the chlorophyll concentration of the current water body is then calculated.

[0012] Furthermore, the analyzing the channel image brightness of the fluorescent image to be tested in different color channels and calculating the chlorophyll concentration of the current water body includes:

[0013] Using a plurality of water samples with known chlorophyll concentrations, a function of the relationship between the chlorophyll concentration and the brightness of the images of different channels is fitted to obtain a concentration calculation formula for the corresponding color channel;

[0014] Determine the best color channel;

[0015] The channel image brightness of the fluorescent image to be measured on the optimal color channel is obtained by analysis, and the chlorophyll concentration is obtained by bringing it into the corresponding concentration calculation formula.

[0016] Furthermore, the optimal color channel is a color channel that minimizes the standard deviation and average error of the relationship function.

[0017] Furthermore, the channel image brightness is the average brightness or regional average brightness of the fluorescent image to be tested on the current set color channel, and the regional average brightness is the average brightness of the current intercepted area obtained by sequentially intercepting and calculating the fluorescent image to be tested according to the set pixel area.

[0018] Furthermore, the step of obtaining the fluorescent image of the water body to be measured under laser irradiation includes:

[0019] Floating the detection device on the surface of a water body, and placing a laser and a camera toward the water body;

[0020] The irradiation angle of the laser is adjusted so that the laser emitted by the laser can effectively excite the chlorophyll in the water body to produce fluorescence;

[0021] Determining that the laser is in a stable working state, turning on the camera to capture a fluorescent image of the water area illuminated by the laser;

[0022] The fluorescence image is processed to obtain the fluorescence image to be tested.

[0023] Beneficial Effects

[0024] Due to the adoption of the above-mentioned technical scheme, the present invention has the following advantages and positive effects compared with the prior art: the present invention uses a camera and a laser to collect laser fluorescence images under the illumination of a light source of a set band, and uses the relationship between the channel image brightness of the laser fluorescence image on different color channels and the chlorophyll concentration to determine the chlorophyll concentration of the water body, providing a new device and method for measuring water quality and the health of aquatic ecosystems, having the advantages of simple structure, easy operation, low cost, wide monitoring range, real-time performance, etc., and can be widely used in environmental monitoring, water resources management, water ecology research and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a front view of a first embodiment of the present invention;

[0026] Figure 2 is a perspective view of a first embodiment of the present invention;

[0027] Figure 3 is a flow chart of a second embodiment of the present invention;

[0028] Figure 4 is a laser fluorescence image of a second embodiment of the present invention;

[0029] Figure 5 It is the laser fluorescence image of each color channel under the condition of no laser and with laser irradiation according to the second embodiment of the present invention;

[0030] Figure 6 This is a curve diagram showing the change in fluorescence image brightness of each color channel with and without laser versus chlorophyll concentration in the second embodiment of the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0032] The first embodiment of the present invention relates to a water chlorophyll detection device based on laser fluorescence and camera, such as Figure 1 , Figure 2 As shown, it includes a laser 4, a camera 5, a sheet metal bracket 3 and a float 1 and a float 2.

[0033] The float 1 and the float 2 are respectively fixed at two ends of the sheet metal bracket 3 to float the entire detection device so that it remains stable on the water surface.

[0034] The laser 4 is fixed to one end of the sheet metal bracket 3 on the downward side. In the embodiment of the present invention, the laser 4 uses a GH04C05Y9G laser tube as a laser light source, emits purple light with a central wavelength of 440nm, and uses a 12V constant current power supply. The laser 4 is sealed to ensure safety and reliability when working underwater. The lens of the laser 4 is a beam-increasing lens, which optimizes the beam quality of the laser 4 and increases the range of laser transmission. After beam intensification, the purple light is irradiated into the water body to be tested.

[0035] The camera 5 is fixed to the other end of the downward side of the sheet metal bracket 3, opposite to the laser. In the implementation of the present invention, the camera adopts the Hackest HK90AP4M color camera with a resolution of 2560×1440 and a video recording frame rate of 30Hz. The camera is also sealed to prevent it from being affected by the underwater environment. The camera 5 is connected to the sheet metal bracket 3 through a hinge, and the shooting range can be adjusted to ensure that the shooting range coincides with the ultraviolet light irradiation range as much as possible.

[0036] The laser 4 and the camera 5 are connected to the terminal respectively, and the terminal controls the opening and closing of the laser 4 and receives the fluorescent image video recorded by the camera 5. The terminal also has a built-in algorithm for calculating the RGB color channel brightness information of the fluorescent image and determining the chlorophyll concentration in different areas of the water body according to the fluorescent brightness distribution information.

[0037] The principle is as follows: using laser as the excitation light source, chlorophyll a will produce 680nm red fluorescence after absorbing the energy of 440nm wavelength purple light. The fluorescent image of the water body is captured by an ordinary color camera. After decomposing the image into RGB monochrome channel images, the brightness of different channels is compared and the relationship between them is positively correlated with the chlorophyll concentration. Then, by measuring the image brightness, the chlorophyll content can be measured quickly and accurately. At the same time, the difference in image brightness in different areas of the image can intuitively reflect the two-dimensional distribution of chlorophyll.

[0038] When in use, the device of the present invention is installed on the surface of water bodies such as rivers and lakes, and the terminal controls the laser to emit purple light and irradiate it into the water body. The camera captures fluorescent image videos within the irradiation range, and the terminal receives and processes these image videos, calculates the RGB color channel brightness information of the fluorescent image through an algorithm, and finally determines the chlorophyll concentration and distribution in the water body.

[0039] The specific operation process is as follows:

[0040] S1: Place the detection device on the surface of a river or lake, turn on the laser and camera, and collect underwater algae fluorescence images;

[0041] The detection device should adjust the position of the float, laser and camera to ensure that they can all be stably placed on the surface of the river or lake to avoid image acquisition deviation caused by water flow or fluctuations;

[0042] The angle and direction of the laser should be adjusted so that it can illuminate the water vertically or at a certain angle to ensure that the laser can effectively stimulate the chlorophyll in the water to produce fluorescence;

[0043] The beam expansion lens of the laser should be adjusted to make its beam emission angle at the optimal position, thereby expanding the laser beam diameter while maintaining the collimation of the beam;

[0044] The laser should be turned on and the power supply current and light intensity should be adjusted to ensure that the laser is in a stable working state and to avoid the influence of unstable laser output on subsequent image acquisition;

[0045] Ordinary color cameras should be waterproofed and connected to the network hard disk through a network cable. After turning on, adjust the focal length and angle of the camera so that it can clearly capture the water area illuminated by the laser and record the fluorescent image of underwater algae.

[0046] The laser tube generally tends to be stable in 4 minutes, so when recording the fluorescent image of underwater algae, it is necessary to ensure that the stable image is collected at least 4-5 minutes after the laser tube is turned on;

[0047] S2: extracting RGB color channels of the algae fluorescence image collected in step S1;

[0048] Fluorescence images should be imported into a computer or image processing device, and screenshots should be obtained through the continuous frame acquisition function of the PotPlayer player, from which clear images such as Figure 4 As shown, analysis is performed.

[0049] Fluorescence images can be decomposed into red (R), green (G), blue (B) and other color channels using the color channel algorithm in the OpenCV library.

[0050] S3: performing image brightness analysis on the algae fluorescence RGB color channel image extracted in step S2 to obtain the brightness of each color channel image;

[0051] The extracted algae fluorescence RGB color channel image is analyzed for brightness using the image brightness algorithm in the OpenCV library;

[0052] The brightness of each color channel image is determined by taking the average brightness of the image channel as the brightness of the current channel, or intercepting the image in sequence according to the set pixel area and calculating the average brightness of the current intercepted area as the average brightness of the image channel;

[0053] S4: Compare the image brightness obtained in step S3 with a pre-calibrated image brightness-chlorophyll concentration relationship model to invert the chlorophyll concentration of the current water body;

[0054] The relationship model between image brightness and chlorophyll concentration should be established in advance. This model can be obtained by calibrating algae solutions with different chlorophyll concentrations in the laboratory.

[0055] The relationship model can be a polynomial regression model, expressed as:

[0056] Y=a n x n +a n-1 x n-1 +……+a2x 2 +a1x+a0;

[0057] Where Y is the prediction result of the polynomial regression model, a0, a1, a2...a n-1 ,a n is the correlation coefficient of the polynomial, x is the brightness of the image channel, and n is the order of the polynomial regression model;

[0058] The order n is determined by the root mean square error and relative error of the evaluation model;

[0059] The brightness values ​​of the RGB color channel images obtained in step S3 should be input into the relational model;

[0060] The model should convert the image brightness value into the corresponding chlorophyll concentration value by calculation;

[0061] The current chlorophyll concentration of the water body should be recorded and displayed in real time, and reports or real-time monitoring data should be generated as needed.

[0062] In this embodiment, the relative distance between the laser and the camera is adjusted according to the specific water environment to ensure that the sheet metal bracket remains as balanced as possible, further improving the accuracy and stability of the measurement.

[0063] Specifically, floats are fixed at both ends of the sheet metal bracket to ensure that the device floats stably on the water surface. The laser and camera are fixed at both ends of the downward side of the sheet metal bracket. By adjusting the hinge between the camera and the sheet metal bracket, the shooting range of the camera can be accurately adjusted to make it overlap as much as possible with the purple light range emitted by the laser.

[0064] The terminal controls the laser switch, receives the fluorescent image video recorded by the camera, processes the image using the built-in algorithm, calculates the brightness information of the RGB color channel, and finally determines the chlorophyll concentration and distribution. During the measurement process, ensure that the laser and camera are sealed effectively to prevent damage to the equipment in the underwater environment.

[0065] The second embodiment of the present invention relates to a method for detecting chlorophyll in water based on laser fluorescence and a camera, which is applied to the device in the first embodiment, such as Figure 3The specific operation process is as follows:

[0066] S1: Place the detection device on the surface of a river or lake, turn on the laser and camera, and collect underwater algae fluorescence images;

[0067] The detection device should adjust the position of the float, laser and camera to ensure that they can all be stably placed on the surface of the river or lake to avoid image acquisition deviation caused by water flow or fluctuations;

[0068] The angle and direction of the laser should be adjusted so that it can illuminate the water vertically or at a certain angle to ensure that the laser can effectively stimulate the chlorophyll in the water to produce fluorescence;

[0069] The beam expansion lens of the laser should be adjusted to make its beam emission angle at the optimal position, thereby expanding the laser beam diameter while maintaining the collimation of the beam;

[0070] The laser should be turned on and the power supply current and light intensity should be adjusted to ensure that the laser is in a stable working state and to avoid the influence of unstable laser output on subsequent image acquisition;

[0071] Ordinary color cameras should be waterproofed and connected to the network hard disk through a network cable. After turning on, adjust the focal length and angle of the camera so that it can clearly capture the water area illuminated by the laser and record the fluorescent image of underwater algae.

[0072] The laser tube generally tends to be stable in 4 minutes, so when recording the fluorescent image of underwater algae, it is necessary to ensure that the stable image is collected at least 4-5 minutes after the laser tube is turned on;

[0073] S2: extracting RGB color channels of the algae fluorescence image collected in step S1;

[0074] Fluorescence images should be imported into a computer or image processing device, and screenshots should be obtained through the continuous frame acquisition function of the PotPlayer player, from which clear images such as Figure 4 As shown, analysis is performed.

[0075] Fluorescence images can be decomposed into red (R), green (G), blue (B) and other color channels using the color channel algorithm in the OpenCV library.

[0076] S3: performing image brightness analysis on the algae fluorescence RGB color channel image extracted in step S2 to obtain the brightness of each color channel image;

[0077] The extracted algae fluorescence RGB color channel image is analyzed for brightness using the image brightness algorithm in the OpenCV library;

[0078] The brightness of each color channel image is determined by taking the average brightness of the image channel as the brightness of the current channel, or intercepting the image in sequence according to the set pixel area and calculating the average brightness of the current intercepted area as the brightness of the image channel;

[0079] S4: Compare the image brightness obtained in step S3 with a pre-calibrated image brightness-chlorophyll concentration relationship model to invert the chlorophyll concentration of the current water body;

[0080] The relationship model between image brightness and chlorophyll concentration should be established in advance. This model can be obtained by calibrating algae solutions with different chlorophyll concentrations in the laboratory.

[0081] The relationship model can be a polynomial regression model, expressed as:

[0082] Y=a n x n +a n-1 x n-1 +……+a2x 2 +a1x+a0;

[0083] Where Y is the prediction result of the polynomial regression model, a0, a1, a2...an-1, an are the correlation coefficients of the polynomial, x is the brightness of the image channel, and n is the order of the polynomial regression model;

[0084] The order n is determined by the root mean square error and relative error of the evaluation model;

[0085] The brightness values ​​of the RGB color channel images obtained in step S3 should be input into the relational model;

[0086] The model should convert the image brightness value into the corresponding chlorophyll concentration value by calculation;

[0087] The current chlorophyll concentration of the water body should be recorded and displayed in real time, and reports or real-time monitoring data should be generated as needed.

[0088] Figure 5-6 The fluorescence image change diagram of each RGB color channel at different concentrations during calibration in this embodiment, the comparison diagram with and without laser irradiation, and the curve diagram of the relationship model are respectively shown. Figure 5 It can be seen that the image of the light-free control group does not change significantly with the increase of concentration, while the fluorescence image of the laser group gradually becomes saturated with the increase of concentration. Through RGB color channel analysis, except for the blue channel, the images of other channels in the laser group gradually become saturated with the increase of concentration, and because chlorophyll a releases 680nm red light after absorbing 440nm purple light, the saturation of the red channel is more obvious, while the images of each color channel of the laser-free control group do not change significantly. Therefore, the effect of introducing laser to excite fluorescence brightness is good. Figure 6It can be seen that the brightness-concentration model of each color channel in the non-laser control group changes irregularly, while the brightness of the red, green, and grayscale channels in the laser irradiation group, except for the blue channel, is positively correlated with the concentration. By comparing the parameters related to the goodness of fit of each color channel model, a suitable color channel model is selected for chlorophyll concentration inversion. In this embodiment, the color channel model with the smallest standard deviation and average error is selected as the optimal channel.

[0089] The above embodiments describe the operation steps and methods of the present invention in detail, and demonstrate the superior performance of the water chlorophyll detection device and method based on laser fluorescence and camera. The present invention has the advantages of simple structure, easy operation, low cost, wide monitoring range, real-time performance, etc., and can play an important role in environmental monitoring, water resources management and water ecology research.

Claims

1. A water body chlorophyll concentration detection device, characterized in that: include: A bracket, one side of which is provided with a buoyancy device, and the other side of which is provided with a laser and a camera; and also includes a control terminal, which controls the laser and the camera to turn on and off to collect the fluorescent image of the water body under laser irradiation to obtain the fluorescent image to be tested, and then analyzes and obtains the channel image brightness of the fluorescent image to be tested in different color channels, and calculates the chlorophyll concentration of the current water body based on the channel image brightness.

2. The detection device according to claim 1, characterized in that: The laser is used to emit violet light with a central wavelength of 440 nm.

3. The detection device according to claim 1, characterized in that: The laser and the camera are respectively placed at two ends of the bracket, and the relative distance between the two is set so that the bracket can maintain balance when floating.

4. The detection device according to claim 1, characterized in that: The camera is connected to the bracket via a hinge, and the shooting area is adjusted via the hinge.

5. A method for detecting chlorophyll concentration in water, characterized in that: Applicable to the detection device as claimed in claims 1-4, The following steps are involved: Acquire the fluorescence image of the water body to be tested under laser irradiation; The channel image brightness of the fluorescent image to be tested in different color channels is analyzed, and the chlorophyll concentration of the current water body is then calculated.

6. The method according to claim 5, characterized in that The analyzing the channel image brightness of the fluorescent image to be tested in different color channels and calculating the chlorophyll concentration of the current water body includes: Using a plurality of water samples with known chlorophyll concentrations, a function of the relationship between the chlorophyll concentration and the brightness of the images of different channels is fitted to obtain a concentration calculation formula for the corresponding color channel; Determine the best color channel; The channel image brightness of the fluorescent image to be measured on the optimal color channel is obtained by analysis, and the chlorophyll concentration is obtained by bringing it into the corresponding concentration calculation formula.

7. The method according to claim 6, characterized in that The optimal color channel is a color channel that minimizes the standard deviation and the average error of the relationship function.

8. The method according to claim 6, characterized in that The channel image brightness is the average brightness or regional average brightness of the fluorescent image to be tested on the current set color channel, and the regional average brightness is the average brightness of the current intercepted area obtained by sequentially intercepting and calculating the fluorescent image to be tested according to the set pixel area.

9. The method according to claim 5, characterized in that The fluorescent image to be measured of the water body under laser irradiation is obtained, include: Floating the detection device on the surface of a water body, and placing a laser and a camera toward the water body; The irradiation angle of the laser is adjusted so that the laser emitted by the laser can effectively excite the chlorophyll in the water body to produce fluorescence; Determining that the laser is in a stable working state, turning on the camera to capture a fluorescent image of the water area illuminated by the laser; The fluorescence image is processed to obtain the fluorescence image to be tested.

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