Three-dimensional fluorescence portable water quality analyzer for pollution component judgment and traceability

Abstract

The present invention discloses a three-dimensional fluorescence portable water quality analyzer for pollution component determination and source tracing, and relates to the technical field of water quality analysis, the analyzer comprises the following components: a sample collection and processing module for collecting a water sample from a to-be-detected water body, filtering to remove impurities, and diluting the water sample according to a self-adaptive dilution multiple algorithm; fluorescence intensity information of a water sample under different excitation wavelengths and emission wavelengths is obtained through the three-dimensional fluorescence detection module, rich three-dimensional fluorescence spectrum data is formed, the real-time fluorescence lifetime imaging module is introduced, and by measuring the fluorescence lifetime of a fluorescent substance and utilizing the principle that different fluorescent substances have different fluorescence lifetime characteristics, the real-time fluorescence lifetime of the water sample is obtained. Various pollution components in the water sample are further distinguished and recognized, the pollution components can be accurately distinguished through fluorescence lifetime measurement and imaging, the accuracy of pollution component judgment is greatly improved, and a reliable basis is provided for accurate treatment of water quality pollution.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water quality analysis, in particular to a three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing. BACKGROUND

[0002] With the accelerated advancement of global industrialization and urbanization, water resources are facing unprecedented pollution challenges. Industrial wastewater discharge, agricultural non-point source pollution, and urban domestic sewage directly discharged into natural water bodies without effective treatment have led to frequent water quality deterioration. These pollutants not only include conventional pollutants such as heavy metals and organic compounds, but also emerging pollutants such as microplastics and drug residues, which pose a serious threat to the ecological environment and human health. In this context, rapid and accurate detection and analysis of pollution components in water have become a key link for water resource protection, ecological environment maintenance, and public health protection. The development of water quality analysis technology is of great significance for identifying pollution sources, assessing pollution levels, developing control strategies, and tracing pollution sources. Traditional water quality analysis methods can meet the detection needs to some extent, but their limitations are increasingly evident when faced with complex and changing pollution situations.

[0003] Traditional water quality analysis methods, such as chemical analysis and chromatographic analysis, have many shortcomings. Chemical analysis is tedious and requires professional personnel and complex equipment, with a long detection process, making it difficult to meet the demand for rapid detection. Chromatographic analysis has high sensitivity and separation ability, but the equipment is expensive, the maintenance cost is high, and the sample pretreatment requirements are high, limiting its widespread application. In addition, traditional methods mainly focus on quantitative analysis of pollutants, and have limited ability to identify and trace the types of pollutants. Three-dimensional fluorescence intensity detection technology, as a new water quality analysis method, can quickly detect fluorescent substances in water, but can only provide intensity information of fluorescent substances, making it difficult to distinguish substances with similar fluorescence spectra, and cannot accurately determine pollution components. In actual detection process, natural light or other light sources in the environment will interfere with fluorescence measurement, leading to inaccurate measurement results, seriously affecting the accuracy of water pollution component determination and tracing. SUMMARY

[0004] The three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing has the advantages that the specially designed sampling mode and pretreatment operation can ensure that the collected water sample is representative and suitable for subsequent detection, the three-dimensional fluorescence detection module can obtain the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths, form three-dimensional fluorescence spectrum data, the real-time fluorescence lifetime imaging module can further distinguish and identify various pollution components in the water sample by measuring the fluorescence lifetime and generate a fluorescence lifetime image, the real-time background fluorescence calibration module can monitor the environmental background fluorescence in real time, deduct the influence of the environmental background fluorescence on the measurement results, improve the measurement accuracy, the data processing and analysis module can comprehensively process and analyze the obtained data, realize qualitative and quantitative analysis of the pollution components and tracing, and the display and output and power module can provide intuitive display of the detection results and convenient data output mode and stable power support.

[0005] The three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing has the advantages that the specially designed sampling mode and pretreatment operation can ensure that the collected water sample is representative and suitable for subsequent detection, the three-dimensional fluorescence detection module can obtain the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths, form three-dimensional fluorescence spectrum data, the real-time fluorescence lifetime imaging module can further distinguish and identify various pollution components in the water sample by measuring the fluorescence lifetime and generate a fluorescence lifetime image, the real-time background fluorescence calibration module can monitor the environmental background fluorescence in real time, deduct the influence of the environmental background fluorescence on the measurement results, improve the measurement accuracy, the data processing and analysis module can comprehensively process and analyze the obtained data, realize qualitative and quantitative analysis of the pollution components and tracing, and the display and output and power module can provide intuitive display of the detection results and convenient data output mode and stable power support. The sample collection and processing module collects a water sample from a water body to be detected, removes impurities through filtration, and dilutes the water sample according to a self-adaptive dilution multiple algorithm. The three-dimensional fluorescence detection module irradiates the water sample with excitation light of different wavelengths, excites the fluorescent substances in the water sample to generate fluorescence, and detects the fluorescence signal to obtain the intensity information of the fluorescent substances in the water sample. The real-time fluorescence lifetime imaging module emits pulsed excitation light to make the fluorescent substances in the water sample emit light, measures the change of the mixed fluorescence signal intensity with time by using a time-resolved detection technology, solves the fluorescence lifetime of each component according to a multi-component fluorescence lifetime separation algorithm formula, generates a fluorescence lifetime image, and thus distinguishes and identifies various pollution components in the water sample. The real-time background fluorescence calibration module monitors the environmental background fluorescence intensity in real time by using a high-precision ambient light sensor, and deducts the background influence from the total measured fluorescence intensity according to a dynamic background deduction algorithm. The data processing and analysis module comprehensively processes the data of the three-dimensional fluorescence detection, real-time fluorescence lifetime imaging and background fluorescence calibration modules, performs qualitative analysis of the pollution components by using a pollution component comprehensive similarity algorithm, and performs quantitative analysis of the pollution components by using a multivariate linear regression model. The display and output and power module is equipped with a high-resolution touch screen display screen to intuitively display the detection results and analysis reports, provides various data output interfaces to facilitate data storage and sharing, uses a rechargeable battery for power supply, and has functions of power monitoring and charging management.

[0006] Further, the sample collection and processing module dilutes the water sample according to an adaptive dilution multiple algorithm, specifically, according to the estimated initial concentration of the water sample and the optimal detection concentration interval of the detection device to determine the dilution multiple , the calculation formula of which is: , if , take , if , if the calculation result is not an integer, take the integer part.

[0007] Further, the three-dimensional fluorescence detection module irradiates the water sample with excitation light of different wavelengths to excite the fluorescent substances in the water sample to produce fluorescence, and detects and records these fluorescence signals. The wavelength of the excitation light can be adjusted according to different detection requirements. High-sensitivity fluorescence detectors are used to capture and convert the fluorescence signals into electrical signals to obtain the actual measured fluorescence intensity. Through multi-angle and multi-wavelength scanning detection of the water sample, the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths is obtained, and the measured fluorescence intensity is compensated according to the fluorescence intensity dynamic compensation formula to form three-dimensional fluorescence spectrum data.

[0008] Further, the three-dimensional fluorescence detection module calculates the fluorescence lifetime and initial fluorescence intensity contribution of each component according to the multi-component fluorescence lifetime separation algorithm formula. Specifically, let the actual measured fluorescence intensity be , the compensated fluorescence intensity be , the temperature influence coefficient be , the humidity influence coefficient be , the temperature and humidity of the current measurement environment be and , the temperature and humidity of the standard measurement environment be and , and the fluorescence intensity dynamic compensation formula be: , wherein and are obtained by measuring standard fluorescent substances under different temperature and humidity conditions and using regression analysis method to fit, and are obtained by real-time measurement of the temperature and humidity sensors, and are the reference environmental conditions for device calibration.

[0009] Further, the real-time fluorescence lifetime imaging module calculates the fluorescence lifetime of each component according to the multi-component fluorescence lifetime separation algorithm formula. Specifically, for multi-component fluorescent substances, the change of the mixed fluorescence signal intensity with time can be represented as: , wherein, measured by a time-correlated single photon counting detector, is the fluorescence lifetime of the fluorescent substance, is the initial fluorescence intensity contribution of the fluorescent substance, is the background noise intensity, estimated by measuring a non-fluorescent sample or the data at the late stage of fluorescence signal decay, is the component number of the fluorescent substance in the water sample, is the time in the fluorescence signal decay process, estimated according to the source and preliminary analysis of the water sample, and adjusted in the fitting process, the above formula is fitted by a non-linear least squares method to solve and , so as to accurately separate the fluorescence lifetime of each component, and generate a fluorescence lifetime image according to the measured fluorescence lifetime information.

[0010] Further, the real-time background fluorescence calibration module monitors the background fluorescence in the environment in real time, automatically removes the influence of the background fluorescence from the measurement data of the three-dimensional fluorescence detection module and the real-time fluorescence lifetime imaging module, uses a high-precision ambient light sensor to detect the intensity and spectral characteristics of the environmental background fluorescence in real time, separates the influence of the environmental background fluorescence from the measurement data through data processing and analysis, and accurately removes it.

[0011] Further, the real-time background fluorescence calibration module separates the influence of the environmental background fluorescence from the measurement data through data processing and analysis, specifically, the intensity and spectral characteristics of the environmental background fluorescence are detected in real time, the background fluorescence intensity measured by the ambient light sensor at time is obtained , the total measured fluorescence intensity is set as a function of time , the fluorescence intensity after background removal is , the dynamic background fluorescence intensity is calculated , wherein is the synchronization time point of the total fluorescence intensity measurement and the background fluorescence calibration, so as to calculate the fluorescence intensity after background removal: , wherein, is the size of the sliding window.

[0012] Further, the data processing and analysis module comprehensively processes the data of the three-dimensional fluorescence detection, real-time fluorescence lifetime imaging and background fluorescence calibration module, and performs qualitative analysis of the pollution components through a pollution component comprehensive similarity algorithm, specifically, the feature vector of the unknown water sample pollution component is , the feature vector of the known pollution component standard sample is , and the weight vector of each feature is , the comprehensive similarity is , the calculation formula is: , wherein, , , is the feature vector of the unknown water sample pollution component, is the feature vector of the known pollution component standard sample, indicates the importance of the first characteristic in the similarity calculation, represent the number of characteristic dimensions participating in the qualitative analysis of the pollution component, and the quantitative analysis of the pollution component is carried out through a multiple linear regression model, specifically, the concentration of the pollution component is , the regression coefficient is , and the concentration calculation formula of the pollution component is: , wherein, is the concentration of the pollution component, is the regression coefficient, which is obtained by regression analysis on the measured data of the standard water sample, is the number of characteristic variables participating in the quantitative analysis of the pollution component.

[0013] Compared with the prior art, the three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing has the following beneficial effects: I. The three-dimensional fluorescence detection module of the present application obtains the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths, forms rich three-dimensional fluorescence spectrum data, and introduces a real-time fluorescence lifetime imaging module. By measuring the fluorescence lifetime of the fluorescent substance, the principle of different fluorescent substances having different fluorescence lifetime characteristics is used to further distinguish and identify various pollution components in the water sample. Through the measurement and imaging of the fluorescence lifetime, these pollution components can be accurately distinguished, greatly improving the accuracy of pollution component determination and providing a reliable basis for accurate management of water pollution.

[0014] II. The present application provides important clues for the tracing of pollution components by comparing and analyzing different water sample data, combining the types, contents and spatial distribution of pollution components and other information. At the same time, the display and output module is equipped with a high-resolution display screen, which can intuitively and clearly display the detection results and analysis report, support touch screen operation, facilitate user interaction and inquiry, and provide multiple data output interfaces. The detection results and analysis report can be output to external devices, which is convenient for data storage, sharing and further processing.

[0015] Other advantages, objects and features of the present application will be set forth in part in the ensuing description, and in part will become apparent to those skilled in the art upon examination of the following, or can be learned by practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0017] Figure 1 It is a structural schematic diagram of a three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing. Figure 2 It is a flow chart of a three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing. DETAILED DESCRIPTION

[0018] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined application purpose, the specific embodiments, structures, features and effects according to the present application will be described in detail below in combination with the drawings and preferred embodiments.

[0019] Embodiment one A river in a city appears water quality deterioration phenomenon, and the environmental protection department suspects that it is caused by the surrounding industrial enterprises discharging sewage, so it is necessary to detect the water samples at different positions of the river to determine the pollution components and trace the pollution source.

[0020] The sample collection and processing module collects water samples at the upstream, midstream, downstream of the river and possibly near the sewage discharge outlet, filters the collected water samples in turn to remove large particle impurities such as silt and leaves, and then determines the dilution multiple of the water sample, estimates the initial concentration of the water sample , which is estimated by analyzing the past water quality data of the river and the sewage discharge characteristics of the surrounding enterprises, and the optimal detection concentration interval of the detection equipment is provided by the equipment manufacturer, according to the adaptive dilution multiple algorithm formula: , if , then , if The calculation result is not an integer, and the upper integer is taken, and the dilution multiple is calculated according to this formula , the water sample is appropriately diluted to prepare for subsequent detection.

[0021] The processed water sample is sent into the three-dimensional fluorescence detection module, a series of excitation light of specific wavelength emitted by the excitation light source is set to irradiate the water sample, the fluorescence detector rapidly captures the fluorescence signal generated by the fluorescent substance in the water sample and converts it into an electric signal, and in the measurement process, environmental temperature, humidity and other factors will affect the fluorescence intensity, the temperature and humidity sensor real-time monitors the temperature Temperature and humidity Temperature influence coefficient Humidity influence coefficient The temperature and humidity of the standard measurement environment are obtained by a large number of measurements of standard fluorescent substances under different temperature and humidity conditions, and are fitted by regression analysis and other methods. The reference environment conditions for equipment calibration are obtained by a large number of measurements of standard fluorescent substances under different temperature and humidity conditions, and are fitted by regression analysis and other methods. The actual measured fluorescence intensity is compensated by the formula to obtain accurate fluorescence intensity data The values of and are preliminarily determined based on experimental measurements and theoretical calculations. The experimental measurements are linear regression analysis of measurements of standard fluorescent substances under different temperature and humidity conditions, and the theoretical calculations are estimates based on the physical and chemical properties of the fluorescent substances and theoretical models. In practical applications, the values are first compared by measuring actual water samples with known concentrations and characteristics. If there is a deviation after compensation, the values of and are adjusted according to the direction and size of the deviation.

[0022] The real-time fluorescence lifetime imaging module emits pulsed excitation light, which excites the fluorescent substances in the water sample. The time-correlated single-photon counting detector accurately measures the arrival time of the fluorescent photons, and the mixed fluorescence signal intensity changes with time The background noise intensity is measured by measuring data of a non-fluorescent sample or after the fluorescence signal decays. The number of components of the fluorescent substances in the water sample is estimated according to the source of the water sample and preliminary analysis, such as considering the types of substances that may be discharged by surrounding enterprises. In the fitting process, the fitting effect under different component numbers is compared to adjust the number of components. According to the multi-component fluorescence lifetime separation algorithm formula: The fluorescence lifetime and the initial fluorescence intensity contribution of each component are solved by nonlinear least squares fitting of the above formula, and a fluorescence lifetime image is generated to visually display the fluorescence lifetime distribution of different positions in the water sample.

[0023] The ambient light sensor in the real-time background fluorescence calibration module continuously monitors the intensity and spectral characteristics of the ambient background fluorescence to obtain the background fluorescence intensity measured by the ambient light sensor at time The dynamic background fluorescence intensity is calculated using the sliding window average method: Recalculating the fluorescence intensity after deducting the background: Wherein, is the total measured fluorescence intensity, is the size of the sliding window, which is determined by experiments, and the algorithm accurately deducts the influence of background fluorescence from the total measured fluorescence intensity, ensuring the accuracy of the measurement data.

[0024] The data processing and analysis module comprehensively processes the data obtained by the above modules, first performs qualitative analysis of the pollution components, and uses the pollution component comprehensive similarity algorithm. Specifically, let the characteristic vector of the unknown water sample be , and the characteristic vector of the known pollution component standard sample be The weight vector of each feature is obtained by measuring and analyzing a large number of known pollution component water samples and stored in the database. There are two ways to preliminarily determine the weight, one is to evaluate the importance of each feature based on practical experience to give the initial weight, and the other is to calculate the variance contribution rate of each feature as the preliminary weight by principal component analysis on a large amount of measurement data, and then according to the formula: Wherein, , , the comprehensive similarity is calculated to preliminarily determine the possible pollution components in the water sample. Then, quantitative analysis of the pollution components is performed, and the concentration of the pollution components is predicted based on the multiple linear regression model. Let the concentration of the pollution component be , and the characteristic variable affecting the concentration be , which is obtained from the processed data, and the regression coefficient is The data pairs of characteristic variables and concentrations are obtained by measuring a large number of known concentration standard water samples, and the least squares method is used to estimate According to the formula: The concentration of the pollution component is quantitatively analyzed, and the regression coefficient is preliminarily determined by the least squares fitting method to make the error sum of squares of the predicted value and the actual value minimum, or by calculating the correlation coefficient between each characteristic variable and the concentration of the pollution component. The stronger the correlation of the characteristic variable, the larger the initial value may be. In the adjustment, the regularization method is used to prevent overfitting, and the size and complexity of the regression coefficient are controlled by adjusting the regularization parameter. At the same time, the evaluation index is used to evaluate the prediction model. If the performance is not ideal, the feature variables are screened or transformed, and the model is fitted again to adjust the regression coefficient.

[0025] The display and output unit clearly shows the test results and analysis reports on a high-resolution screen, including information such as the types and concentrations of pollutants and their spatial distribution in the river. Environmental protection staff can operate the touch screen to query relevant data in detail and output the test results and analysis reports to a computer via USB interface for further research and report writing.

[0026] By detecting and analyzing water samples from different locations along the river, it was determined that the main pollutant in the river is a certain type of organic compound. It was found that the concentration of this pollutant in the downstream water sample was significantly higher than that in the upstream. At the same time, the concentration of this pollutant was extremely high in the water sample near the sewage outlet of a certain enterprise. Based on the comprehensive similarity analysis results, it can be basically determined that the enterprise is the main source of river pollution.

[0027] Example 2 A large drinking water source is responsible for supplying drinking water to millions of residents in surrounding cities. In order to ensure the safety of residents' drinking water, it is necessary to conduct high-frequency and high-precision regular monitoring of the water quality of the source, promptly identify potential pollution risks, and ensure the quality and safety of residents' water use.

[0028] According to the sampling plan, water samples were collected from multiple key areas of the drinking water source using the sample collection and processing module of the water quality analyzer, including but not limited to the water intake, the center of the reservoir, the confluence of rivers, and areas where pollution sources may exist. To ensure the representativeness of the collected water samples, samples were also collected at different depths (surface, middle layer, and bottom layer). The collected water samples were first coarsely filtered to remove larger impurities such as branches and aquatic plants. Then, they were filtered a second time through a precision filter to remove small suspended solids and impurities. Afterward, based on the estimated initial concentration of the water sample (estimated by comprehensively considering factors such as long-term historical monitoring data of the water source, surrounding industrial distribution, agricultural activities, and recent weather changes) and the optimal detection concentration range of the detection equipment, the dilution factor was accurately calculated using an adaptive dilution factor algorithm, and the water sample was accurately diluted to ensure that the water sample concentration was within the optimal sensitivity range of the detection equipment.

[0029] The processed water sample is carefully placed into the three-dimensional fluorescence detection module. According to the characteristics of the possible pollutants in the water source, the excitation light source is precisely set to emit a series of specific wavelengths of excitation light, so that the fluorescent substances in the water sample can fully produce fluorescence. The high-sensitivity fluorescence detector rapidly and accurately captures the fluorescence signals generated by the fluorescent substances in the water sample and efficiently converts them into electrical signals. At the same time, the temperature and humidity sensor monitors the temperature and humidity changes in the measurement environment in real time and accurately. The data processing system considers the temperature influence coefficient, humidity influence coefficient, and the temperature and humidity of the current measurement environment and the standard measurement environment, and finely calibrates and compensates the actual measured fluorescence intensity according to the fluorescence intensity dynamic compensation formula, so as to obtain accurate and reliable fluorescence intensity data.

[0030] The real-time fluorescence lifetime imaging module emits stable and accurate pulsed excitation light, which uniformly irradiates the water sample, so that the fluorescent substances in the water sample are fully excited. The time-correlated single-photon counting detector accurately measures the arrival time of fluorescent photons due to its ultra-high sensitivity and accurate time resolution. Through the use of multi-component fluorescence lifetime separation algorithm, the change of mixed fluorescence signal intensity with time is deeply and carefully fitted and analyzed, not only the fluorescence lifetime and initial fluorescence intensity contribution of each component are accurately separated, but also the relative content of each component is accurately calculated, and high-resolution, clear and intuitive fluorescence lifetime images are generated, which provides a strong visual basis for analysts to deeply understand the characteristics of fluorescent substances in water samples.

[0031] The ambient light sensor always maintains a high-sensitivity working state, and continuously monitors the intensity and spectral characteristics of the environmental background fluorescence in real time. The real-time background fluorescence calibration module uses advanced dynamic background subtraction algorithm to analyze and process the data collected by the ambient light sensor in real time, accurately calculates the dynamic background fluorescence intensity using sliding window averaging method, and accurately subtracts the influence of background fluorescence from the total measured fluorescence intensity, thereby maximizing the authenticity and reliability of the measurement data.

[0032] The data processing and analysis module comprehensively and deeply processes the massive data obtained by the above modules. First, the comprehensive similarity algorithm of pollution components is used to compare the unknown water sample feature vector obtained by measurement with the feature vector of the known standard sample of common drinking water pollution components. According to the principal component analysis, the feature weights are continuously adjusted and optimized according to the cross-validation and long-term monitoring data feedback in practical application, the comprehensive similarity is accurately calculated, so that the existence of potential pollution components and the possible pollution component categories in the water sample can be accurately judged. Then, the pollution component concentration prediction formula is used to perform high-precision quantitative analysis on the possible pollution components based on the multiple feature variables (such as fluorescence intensity, fluorescence lifetime, etc.) affecting the concentration and the regression coefficients estimated by the strict least square method, and accurately determine whether the concentration is within the safe range, thereby providing scientific and accurate data support for the comprehensive evaluation of water quality.

[0033] The display and output unit clearly displays the detailed and comprehensive detection results and analysis report on the high-resolution display screen in an intuitive and easy-to-understand manner. The content includes the overall evaluation of water quality, the existence of pollution components, the types of pollution components, the concentration, and the distribution of pollution components in different regions of the water source, etc. The staff can flexibly and conveniently operate the touch screen to query and analyze the related data in detail. At the same time, the system also supports real-time uploading of the results to the server of the monitoring center through the high-speed network interface, realizing remote storage, sharing and real-time monitoring of data, facilitating further research, analysis and management decision-making by professionals. In addition, the detection results and analysis report can also be output to external storage devices through the USB interface, which is convenient for data backup and offline analysis.

[0034] After comprehensive and detailed detection and analysis of the water sample in the drinking water source, no obvious pollution components are found, and all indicators meet the national drinking water standards.

[0035] The above is only a preferred embodiment of the present application, and does not limit the present application in any form. Although the present application has been disclosed as above with a preferred embodiment, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the scope of the technical solution of the present application. Any modification, change, equivalent change and modification of the above embodiments made according to the technical essence of the present application are still within the scope of the technical solution of the present application.

Claims

1. A three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing, characterized in that, The water quality analyzer comprises the following components: A sample collection and processing module: water samples are collected from the water body to be tested, filtered to remove impurities, and then diluted according to an adaptive dilution multiple algorithm; A three-dimensional fluorescence detection module: different wavelengths of excitation light are emitted to irradiate the water sample, excite the fluorescent substances in the water sample to generate fluorescence, and detect the fluorescence signals to obtain the intensity information of the fluorescent substances in the water sample; A real-time fluorescence lifetime imaging module: pulsed excitation light is emitted to make the fluorescent substances in the water sample emit light, the time-resolved detection technology is used to measure the change of the mixed fluorescence signal intensity with time, and the fluorescence lifetime of each component is solved according to the multi-component fluorescence lifetime separation algorithm formula, so as to generate a fluorescence lifetime image and distinguish and identify various pollution components in the water sample; A real-time background fluorescence calibration module: a high-precision ambient light sensor is used to monitor the intensity of the environmental background fluorescence in real time, and the background influence is deducted from the total measured fluorescence intensity according to a dynamic background deduction algorithm; A data processing and analysis module: the data of the three-dimensional fluorescence detection, real-time fluorescence lifetime imaging and background fluorescence calibration modules are comprehensively processed, the pollution component qualitative analysis is performed through a pollution component comprehensive similarity algorithm, and the pollution component quantitative analysis is performed through a multivariate linear regression model; A display, output and power module: a high-resolution touch screen display screen is provided to visually display the detection results and analysis report, and various data output interfaces are provided to facilitate data storage and sharing, and a rechargeable battery is used for power supply and has the functions of power monitoring and charging management.

2. The three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing according to claim 1, characterized in that, The sample collection and processing module dilutes the water sample according to an adaptive dilution multiple algorithm, specifically, according to the estimated initial concentration of the water sample and the optimal detection concentration interval of the detection equipment to determine the dilution multiple , the calculation formula of which is: If , then take If , the calculation result is not an integer, then take the integer part.

3. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of origin according to claim 1, characterized in that, The three-dimensional fluorescence detection module emits excitation light of different wavelengths to irradiate the water sample, excites the fluorescent substances in the water sample to generate fluorescence, detects and records these fluorescence signals, adjusts the wavelength of the excitation light according to different detection requirements, captures and converts the fluorescence signals by using a high-sensitivity fluorescence detector, converts the fluorescence signals into electrical signals, obtains the actual measured fluorescence intensity, performs multi-angle and multi-wavelength scanning detection on the water sample, obtains the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths, compensates the measured fluorescence intensity according to a fluorescence intensity dynamic compensation formula, and forms three-dimensional fluorescence spectrum data.

4. The three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing according to claim 3, characterized in that, The three-dimensional fluorescence detection module solves the fluorescence lifetime and initial fluorescence intensity contribution of each component according to a multi-component fluorescence lifetime separation algorithm formula. Specifically, let the actual measured fluorescence intensity be , the compensated fluorescence intensity be , the temperature influence coefficient be , the humidity influence coefficient be , the temperature and humidity of the current measurement environment be and , the temperature and humidity of the standard measurement environment be and , and the fluorescence intensity dynamic compensation formula be , wherein and are obtained by measuring the standard fluorescent substance under different temperature and humidity conditions and using a regression analysis method to fit and are obtained by real-time measurement of the temperature and humidity sensors, and are the reference environmental conditions for device calibration.

5. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of origin according to claim 1, characterized in that, The real-time fluorescence lifetime imaging module solves the fluorescence lifetime of each component according to a multi-component fluorescence lifetime separation algorithm formula, and specifically, for multi-component fluorescent substances, the mixed fluorescence signal intensity changes with time Can be expressed as: Wherein, Measured by a time-dependent single photon counting detector, The fluorescence lifetime of the first The fluorescence lifetime of the first The initial fluorescence intensity contribution of the first The initial fluorescence intensity contribution of the first The background noise intensity is estimated by measuring a non-fluorescent sample or data in the late stage of fluorescence signal decay, The number of components of the fluorescent substance in the water sample, The time in the fluorescence signal decay process is estimated according to the source and preliminary analysis of the water sample, and is adjusted in the fitting process, and the above formula is fitted by a non-linear least squares method to solve And Thus, the fluorescence lifetime of each component is accurately separated, and a fluorescence lifetime image is generated according to the measured fluorescence lifetime information.

6. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of origin according to claim 1, characterized in that, The real-time background fluorescence calibration module monitors the background fluorescence in the environment in real time, automatically deducts the influence of the background fluorescence from the measurement data of the three-dimensional fluorescence detection module and the real-time fluorescence lifetime imaging module, uses a high-precision ambient light sensor to detect the intensity and spectral characteristics of the environmental background fluorescence in real time, separates and accurately deducts the influence of the environmental background fluorescence from the measurement data through data processing and analysis.

7. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of origin according to claim 6, characterized in that, The real-time background fluorescence calibration module separates the influence of the environmental background fluorescence from the measurement data through data processing and analysis. Specifically, the intensity and spectral characteristics of the environmental background fluorescence are detected in real time to obtain the environmental light sensor at time measured background fluorescence intensity Let the total measured fluorescence intensity change over time be The background-corrected fluorescence intensity is The dynamic background fluorescence intensity is calculated by wherein is the total fluorescence intensity measurement and the background fluorescence calibration synchronization time point, so as to calculate the background-corrected fluorescence intensity: wherein, is the size of the sliding window.

8. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of origin according to claim 1, characterized in that, The data processing and analysis module comprehensively processes data from the three-dimensional fluorescence detection, real-time fluorescence lifetime imaging, and background fluorescence calibration modules. It performs qualitative analysis of pollutant components using a comprehensive similarity algorithm. Specifically, the feature vector of the unknown water sample pollutant component is set as follows: The feature vector of the known pollutant component standard sample is: The weight vectors of each feature are: The overall similarity is The calculation formula is: ,in, , , It is the feature vector of unknown water sample pollutants. It is the feature vector of a standard sample of known pollutant components. Indicates the first The importance of each feature in similarity calculation This represents the number of characteristic dimensions involved in the qualitative analysis of pollutants, and the quantitative analysis of pollutants is performed using a multiple linear regression model. Specifically, let the concentration of the pollutant be... The regression coefficient is The formula for calculating the concentration of its pollutants is: ,in, It refers to the concentration of pollutants. These are regression coefficients, obtained through regression analysis of measurement data from standard water samples. It is the number of characteristic variables involved in the quantitative analysis of pollutant components.

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