A kind of floating algae detection device and detection method

Abstract

The present invention discloses a phytoplankton detection device and method, including a system control unit, which has a polychromatic light source, a sampling component and a fluorescence detector; a detection component, which has an excitation fiber radiating unit and an emission fiber detecting unit, wherein the excitation fiber radiating unit includes an optical fiber jumper 1 and a multimode fiber bundle 1 coupled to the polychromatic light source, and the emission fiber detecting unit includes an optical fiber jumper 2 and a multimode fiber bundle 2 coupled to the fluorescence detector; wherein the excitation fiber radiating unit collects the wide-band optical signal of the polychromatic light source to the sample to be tested of the sampling unit, and collects the wide-band fluorescence signal of the sample to be tested to the fluorescence detector through the emission fiber detecting unit. The present invention realizes the detection of phytoplankton within a regional range by adopting the excitation fiber radiating unit and the emission fiber detecting unit, which fundamentally eliminates the interference of the external environment and improves the signal-to-noise ratio of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of phytoplankton detection, and in particular to a phytoplankton detection device and a detection method. Background Art

[0002] As the most important primary producer in water bodies and the source of the food chain, phytoplankton is a comprehensive indicator of the health of water bodies, fundamentally affecting the global biogeochemical cycle and climate change. Therefore, the production and distribution of phytoplankton in water bodies is an important indicator for evaluating the eutrophication of water bodies. For excessively rampant algal communities, the water environment will eventually form a freshwater "water bloom" or a marine "red tide", and the damage caused mainly includes the following aspects:

[0003] 1: Deplete the dissolved oxygen in the water, causing the death of a large number of aquatic organisms such as fish;

[0004] 2: Damage to the environment and landscape;

[0005] 3: Excessive phytoplankton residues degrade, making the water black and smelly, making it undrinkable;

[0006] 4: Some phytoplankton release algal toxins into the water, posing a serious threat to human health.

[0007] At present, fluorescence detection technology is widely used to detect the content of chlorophyll a in algae. Through a specific light wave excitation method, the chlorophyll a content in water can be detected quickly and non-destructively. It is of great significance in the fields of water environment monitoring, water ecological environment early warning system, lake and river eutrophication detection, and water body comprehensive toxicity identification. Conventional algae monitoring equipment can only measure the overall content of phytoplankton or identify a single algae class and measure the concentration of a single algae class, and the measurement results are very unstable and greatly affected by the outside world, so it cannot meet the real-time online monitoring function of the growth status of phytoplankton communities.

[0008] With the development of society, the healthy development of the water ecological environment has attracted more and more attention from the public. For example, due to eutrophication, large-scale "blue algae" will break out every year in Taihu Lake and Chaohu Lake, causing great losses to the surrounding industrial and agricultural production and causing serious harm to people's lives and health. For the measurement and early warning of phytoplankton, conventional water quality monitoring equipment cannot meet the needs of human production and life in terms of measurement range and accuracy. The market urgently needs a device that can not only meet the content of phytoplankton in the water body, but also can realize the identification of algae communities and root measurement. Because the main way to control the harm of phytoplankton is "control growth" + "early warning". Early warning is divided into short-term warning and medium- and long-term warning. Short-term warning is to collect phytoplankton concentration information at the monitoring point in real time, and issue early warning information of algae outbreak when the phytoplankton concentration reaches a certain warning line. This short-term warning usually occurs on the eve of a large algae outbreak, and the time left for relevant departments to take countermeasures is also very short. The medium- and long-term warning is based on the real-time measurement of phytoplankton population concentration combined with hydrological and water quality parameters and certain meteorological parameters (such as temperature, wind direction, wind speed, etc.) to form a "water bloom" or "red tide" prediction mathematical model, predicting the growth of phytoplankton populations over a long period of time in the future, and fundamentally solving the problem of algal eutrophication. Summary of the invention

[0009] The purpose of the present invention is to provide a phytoplankton detection device and a detection method to solve the problems raised in the above background technology.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] A phytoplankton detection device includes a system control component having a polychromatic light source, a sampling component and a fluorescence detector; a detection component having an excitation fiber radiating component and an emission fiber detecting component, wherein the excitation fiber radiating component includes an optical fiber jumper 1 and a multimode optical fiber bundle 1 coupled to the polychromatic light source, and the emission fiber detecting component includes an optical fiber jumper 2 and a multimode optical fiber bundle 2 coupled to the fluorescence detector; wherein the excitation fiber radiating component collects the wide-band optical signal of the polychromatic light source onto a sample to be detected in the sampling component, and collects the wide-band fluorescence signal of the sample to be detected onto the fluorescence detector through the emission fiber detecting component.

[0012] The multimode optical fiber bundle 1 and the multimode optical fiber bundle 2 are made of the same material, and the number and cross-sectional area of ​​the multimode optical fiber bundle 1 are not greater than the number and cross-sectional area of ​​the multimode optical fiber bundle 2.

[0013] The output end of the emission optical fiber detection component is placed vertically to the output end of the excitation optical fiber radiation component.

[0014] The distance between the transmitting optical fiber detection component and the sample to be tested is 0-3 cm.

[0015] The distance between the excitation optical fiber detection component and the sample to be tested is 0-3 cm.

[0016] A method for detecting phytoplankton comprises the following detection steps:

[0017] Step 1: Acquire characteristic fluorescence distribution data of standard algae groups, wherein the characteristic fluorescence distribution data of standard algae groups includes characteristic fluorescence spectrum analysis data of each algae;

[0018] Step 2: Place the sampling components at preset positions within the area to be detected and take samples respectively;

[0019] Step 3: irradiate the area to be detected by the excitation optical fiber radiation component, and transmit the fluorescence signal to the fluorescence detector through the emission optical fiber detection component of the area to be detected, so as to obtain the light intensity signal of different light bands;

[0020] Step 4: The light intensity signals of different light bands are combined with the characteristic light intensity superposition theorem and the standard algae characteristic fluorescence distribution data to determine the algae fluorescence intensity distribution data within the detection area, and the algae fluorescence intensity distribution data contains the total fluorescence intensity and the characteristic fluorescence intensity;

[0021] Step 5: determining the total content data of algae within the detection area according to the total fluorescence intensity, and determining the data of different algae classes and the content data of different algae classes contained in the detection area according to the characteristic fluorescence intensity;

[0022] Step 6: Display the data in step 5.

[0023] The method for obtaining the characteristic fluorescence distribution data of the standard algae group comprises the following steps:

[0024] Step 11: Cultivate standard solutions of various algae, which are pure solutions of a single algae with a preset concentration;

[0025] Step 12: Obtain the chlorophyll a concentration of each algae class by international standard spectrophotometry;

[0026] Step 13: Measure each algae type by using a phytoplankton detection device to obtain fluorescence spectrum distribution data of each algae unit concentration, and normalize the data;

[0027] Step 14: Analyze the fluorescence spectrum data of each algae class based on the three-dimensional data processing algorithm, and determine the characteristic fluorescence spectrum distribution data of each algae;

[0028] Step 15: Determine the characteristic fluorescence distribution data of the standard algae group through the characteristic fluorescence spectrum distribution data of each algae.

[0029] It can be seen from the above technical solution that the present invention realizes the detection of phytoplankton within the regional range by adopting the excitation optical fiber radiation element and the emission optical fiber detection element, which fundamentally eliminates the interference of the external environment and improves the signal-to-noise ratio of the system. The specific beneficial effects are as follows:

[0030] 1: The uniqueness of optical fiber replaces the traditional free space complex optical system design, eliminates external environmental interference and improves the system signal-to-noise ratio. Due to the simplified structure, the economic benefits of the product are further improved.

[0031] 2: Realize online detection of long-distance algal communities on a grid basis, which can not only measure the total amount of phytoplankton, but also detect the concentration classification of algal communities, and has good application prospects in water eutrophication or algal bloom early warning monitoring.

[0032] 3: The fluorescence intensity distribution data of algae groups can be obtained through the superposition effect of characteristic fluorescence intensity. Compared with the traditional full-spectrum analysis method, it avoids the redundant calculation of data, shortens the analysis time of a large amount of irrelevant data, simplifies the algorithm and improves the accuracy and measurement efficiency of the system;

[0033] 4: The sampling components used can have automatic sampling, automatic cleaning, and automatic waste discharge functions, which can meet the application requirements of real-time online water environment detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic block diagram of the structure of the device of the present invention. DETAILED DESCRIPTION

[0035] The present invention will be further described below in conjunction with the accompanying drawings:

[0036] See also Figure 1 This case provides a phytoplankton detection device, including a system control component and a detection component, specifically, including:

[0037] The system control component has a complex light source 15, a sampling component and a fluorescence detector 16. The system control component described here also includes a driving circuit 13, a signal processor 14, a controller 12 and a host computer software system 11. Specifically, the host computer software system 11 is connected to the controller 12, and the controller 12 is respectively connected to the driving circuit 13, the sampling component and the signal processor 14, the driving circuit 13 is connected to the complex light source 15, and the signal processor 14 is connected to the fluorescence detector 16; here, the sampling component includes a pump component 17, a cleaning component 18 and a valve component 19, and the controller 12 is respectively connected to the pump component 17, the cleaning component 18 and the valve component 19. When collecting the sample to be tested, the pump component 17 is controlled by the controller 12 to provide the sample to be tested to a preset position. After the test is completed, the waste pipe valve is activated by the valve component 19 to discharge the waste water by gravity. After emptying, the pump component 17 and the valve component 19 are controlled by the controller 12 to switch the system flow path, and the cleaning liquid is injected into the preset position, and finally emptied in the same way.

[0038] The detection component has an excitation fiber radiation component 21 and an emission fiber detection component 22. The excitation fiber radiation component 21 includes an optical fiber jumper 212 and a multimode fiber bundle 211 coupled to the polychromatic light source 15, and the emission fiber detection component 22 includes an optical fiber jumper 222 and a multimode fiber bundle 221 coupled to the fluorescence detector 16. Specifically, the excitation fiber radiation component 21 has a collimation and convergence effect, and the wide-band light signal of the polychromatic light source 15 is transmitted and converged to the sample 23 to be tested. The emission fiber detection component 22 has a collimation and convergence effect, and the wide-band fluorescence signal transmitted at a vertical angle to the radiation light path of the excitation fiber radiation component 21 is collected into the system control component 1, so as to realize the detection of the full optical fiber optical path system, that is, to realize the detection of phytoplankton. Here, the input end of the emission fiber detection component 22 is placed vertically to the output end of the excitation fiber radiation component 21. The effect of this placement is that it can prevent the main optical path of the system from causing background interference to the weak fluorescence detection.

[0039] Furthermore, the multimode optical fiber bundle 1 211 and the multimode optical fiber bundle 2 221 are made of the same material, and the number and cross-sectional area of ​​the multimode optical fiber bundle 1 211 are not greater than the number and cross-sectional area of ​​the multimode optical fiber bundle 2 221. This arrangement can further improve the detection of weak fluorescence signals of the system by reducing the emission wide angle of the excitation optical fiber radiation component 21 to increase the detection wide angle of the emission optical fiber detection component 22.

[0040] Furthermore, the distance between the transmitting optical fiber detection element 22 and the sample to be tested is 0-3 cm. This setting can further ensure the detection efficiency and transmission loss of weak optical signals, and prevent interference from free space optical fibers.

[0041] Furthermore, the distance between the excitation optical fiber detector 21 and the sample to be tested is 0-3 cm. This setting can further ensure the detection efficiency and transmission loss of weak optical signals, and prevent interference from free space optical fibers.

[0042] In this embodiment, the phytoplankton detection device also has a phytoplankton detection method, and the detection steps include the following:

[0043] Step 1: Obtain characteristic fluorescence distribution data of standard algae groups, wherein the characteristic fluorescence distribution data of standard algae groups includes characteristic fluorescence spectrum analysis data of each algae. Specifically, the method for obtaining characteristic fluorescence distribution data of standard algae groups is:

[0044] S11: Standard solution for culturing various algae, which is a single algae pure solution with a preset concentration;

[0045] S12: Obtain the chlorophyll a concentration of each algae class by international standard spectrophotometry;

[0046] S13: Measure each algae class by means of the phytoplankton detection equipment, obtain the fluorescence spectrum distribution data of each algae unit concentration, and normalize the data. In the detection process, various algae are obtained respectively by the sampling assembly, based on the collimation and convergence effect of the excitation optical fiber radiation component 21, the wide-band light signal of the polychromatic light source 15 is transmitted and collected on each algae, and the emission optical fiber detection component 22 has a collimation and convergence effect, and the wide-band fluorescence signal transmitted at the vertical angle of the radiation light path of the excitation optical fiber radiation component 21 is collected to the fluorescence detector 16, and then successively passed through the signal processor 14 and the controller 12 and transmitted to the upper computer software system 11, so as to obtain the fluorescence spectrum distribution data of each algae unit concentration. The data normalization processing used here can be understood by those skilled in the art as that the data normalization processing used includes two forms, one is to convert the number into a decimal between (0, 1), and the other is to convert the dimensionless expression into a dimensionless expression. Mainly for the convenience of data processing, the data is mapped to the range of 0-1 for processing, which is more convenient and fast.

[0047] S14: Analyze the fluorescence spectrum data of each algae class based on a three-dimensional data processing algorithm (UVE uninformative variable elimination method or PARAFAC method), and determine the characteristic fluorescence spectrum distribution data of each algae.

[0048] S15: Determine the characteristic fluorescence distribution data of the standard algae group through the characteristic fluorescence spectrum distribution data of each algae.

[0049] Step 2: Place the sampling components at the preset positions within the area to be detected and collect samples respectively. Here, based on the sampling process within the area to be detected, it is necessary to combine the phytoplankton detection equipment used in this case, as follows:

[0050] First, each module of the phytoplankton detection equipment is installed at a preset position, including a sampling component and a system control component 1 for controlling the sampling component, wherein the sampling component is placed at a preset position within the area to be detected, wherein the pump component 17 is controlled by the controller 12, and the sample 23 to be tested is provided to the preset position; then, the driving circuit 13 is triggered by the controller 12 to simultaneously light up the polychromatic light source 15, and the light intensity of the polychromatic light source 15 is kept in a stable state.

[0051] Step 3: The area to be detected is radiated by the excitation optical fiber radiation element 21, and the fluorescence signal is transmitted to the fluorescence detector 16 through the emission optical fiber detection element 22 of the area to be detected, so as to obtain the light intensity signal of different optical bands. Here, the fluorescence signal is subjected to photoelectric conversion and spectral analysis by the fluorescence detector 16, and the spectral data is input into the signal processor 14 for further processing, and the light intensity of different optical bands is measured according to the number of signal pulses of different optical bands.

[0052] Step 4: The light intensity signals of different light bands are combined with the characteristic light intensity superposition theorem to determine the fluorescence intensity distribution data of the algae within the detection area, and the algae fluorescence intensity distribution data contains the total fluorescence intensity and the characteristic fluorescence intensity. Here, in practice, the detection data of the controller 12 of the lower computer is obtained through the upper computer software system 11, so as to obtain the characteristic fluorescence distribution data of the algae.

[0053] Step 5: Determine the total algae content data within the detection area according to the total fluorescence intensity, and determine the different algae category data and content data of different algae categories within the detection area according to the characteristic fluorescence intensity. Here, those skilled in the art can understand that there is a good correspondence between the distribution of algae community fluorescence intensity and the algae community concentration and algae category, that is, the total fluorescence intensity can be used to invert the total algae content, and the characteristic fluorescence intensity can be used to invert the different algae category data and content data of different algae categories, ultimately achieving the classification measurement of algae community concentration;

[0054] Step 5: Display the final measurement results on the upper interface.

[0055] It should be pointed out that the distribution of algal fluorescence intensity has a good correspondence with the algal community concentration and algal phylum, which can be obtained by the following steps:

[0056] S51: Based on the characteristic fluorescence distribution data of the standard algae group, the characteristic fluorescence distribution model of the sample to be tested is obtained using the phytoplankton detection equipment of this case;

[0057] S52: Based on the characteristic light intensity superposition theorem, the characteristic fluorescence distribution model of the sample to be tested is formed by superimposing the characteristic light spectrum distribution of multiple standard algae communities;

[0058] S53: using multivariate linear fitting or matrix algorithm model to sum the fluorescence intensity of each feature point;

[0059] S54: Assuming that the coefficient value of the standard brick algae community is less than 0, the value of the algae category is set to 0, that is, the chlorophyll a of the phytoplankton of the algae category is set to 0, that is, the test solution does not contain this type of algae;

[0060] S55: removing the spectral characteristics of the standard algae of the algae in the subsequent algorithm, and repeating step S53 to obtain the concentration of chlorophyll a of the remaining algae;

[0061] S56: Assume that the coefficient values ​​of the standard algae community are all greater than 0, that is, the test solution contains this algae class, and calculate the chlorophyll a concentration of each algae respectively;

[0062] S57: according to the coefficient value of the standard algae community and algae obtained in S54, S55 or S56, that is, the test solution contains the algae, and the concentration of chlorophyll a of various algae is calculated respectively;

[0063] S58: Based on the calculation results of S57, the classification measurement of algae group concentration is finally achieved, and the calculation results are displayed on the upper interface.

[0064] The embodiments described above are merely descriptions of preferred implementation modes of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A phytoplankton detection device, characterized in that: include: a system control unit having a polychromatic light source, a sampling assembly, and a fluorescence detector; It also includes a driving circuit (13), a signal processor (14), a controller (12) and a host computer software system (11), wherein the host computer software system (11) is connected to the controller (12), the controller (12) is respectively connected to the driving circuit (13), the sampling component and the signal processor (14), the driving circuit (13) is connected to a complex light source (15), and the signal processor (14) is connected to a fluorescence detector (16); The sampling assembly comprises a pump assembly (17), a cleaning assembly (18) and a valve assembly (19), and the controller (12) is connected to the pump assembly (17), the cleaning assembly (18) and the valve assembly (19) respectively; The detection component comprises an excitation optical fiber radiation component and an emission optical fiber detection component, wherein the excitation optical fiber radiation component comprises an optical fiber jumper 1 coupled to a complex light source and a multimode optical fiber bundle 1, and the emission optical fiber detection component comprises an optical fiber jumper 2 coupled to a fluorescence detector and a multimode optical fiber bundle 2; The excitation optical fiber radiation component collects the broadband light signal of the polychromatic light source onto the sample to be tested in the sampling component, and collects the broadband fluorescence signal of the sample to be tested onto the fluorescence detector through the emission optical fiber detection component.

2. A phytoplankton detection device according to claim 1, characterized in that: The multimode optical fiber bundle 1 and the multimode optical fiber bundle 2 are made of the same material, and the number and cross-sectional area of ​​the multimode optical fiber bundle 1 are not greater than the number and cross-sectional area of ​​the multimode optical fiber bundle 2.

3. The phytoplankton detection device according to claim 1, characterized in that: The output end of the emission optical fiber detection component is placed vertically to the output end of the excitation optical fiber radiation component.

4. The phytoplankton detection device according to claim 1, characterized in that: The distance between the transmitting optical fiber detection component and the sample to be tested is 0-3 cm.

5. The phytoplankton detection device according to claim 1, characterized in that: The distance between the excitation optical fiber radiation element and the sample to be tested is 0-3 cm.

6. A method for detecting phytoplankton according to any one of claims 1 to 5, characterized in that: The following detection steps are included: Step 1: Acquire characteristic fluorescence distribution data of standard algae groups, wherein the characteristic fluorescence distribution data of standard algae groups includes characteristic fluorescence spectrum analysis data of each algae; Step 2: Place the sampling components at preset positions within the area to be detected and take samples respectively; Step 3: irradiate the area to be detected by the excitation optical fiber radiation component, and transmit the fluorescence signal to the fluorescence detector through the emission optical fiber detection component of the area to be detected, so as to obtain the light intensity signal of different light bands; Step 4: The light intensity signals of different light bands are combined with the characteristic light intensity superposition theorem and the standard algae characteristic fluorescence distribution data to determine the algae fluorescence intensity distribution data within the detection area, and the algae fluorescence intensity distribution data contains the total fluorescence intensity and the characteristic fluorescence intensity; Step 5: determining the total content data of algae within the detection area according to the total fluorescence intensity, and determining the data of different algae classes and the content data of different algae classes contained in the detection area according to the characteristic fluorescence intensity; Step 6: Display the data in step 5.

7. The method for detecting phytoplankton detection equipment according to claim 6, characterized in that: The method for obtaining the characteristic fluorescence distribution data of the standard algae group comprises the following steps: Step 11: Cultivate standard solutions of various algae, which are pure solutions of a single algae with a preset concentration; Step 12: Obtain the chlorophyll a concentration of each algae class by international standard spectrophotometry; Step 13: Measure each algae type by using a phytoplankton detection device to obtain fluorescence spectrum distribution data of each algae unit concentration, and normalize the data; Step 14: Analyze the fluorescence spectrum data of each algae class based on the three-dimensional data processing algorithm, and determine the characteristic fluorescence spectrum distribution data of each algae; Step 15: Determine the characteristic fluorescence distribution data of the standard algae group through the characteristic fluorescence spectrum distribution data of each algae.

Images