Three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing

Abstract

The application discloses a three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing, and relates to the technical field of water quality analysis.The analyzer comprises the following components: a sample collection and treatment module, which collects a water sample from a water body to be measured, removes impurities through filtration, and dilutes the water sample according to a self-adaptive dilution multiple algorithm; the three-dimensional fluorescence detection module is used to obtain fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths, form rich three-dimensional fluorescence spectrum data, and introduce a real-time fluorescence lifetime imaging module; the fluorescence lifetime of fluorescent substances is measured; the principle that different fluorescent substances have different fluorescence lifetime characteristics is used; various pollution components in the water sample are further distinguished and identified; the pollution components can be accurately distinguished through the measurement and imaging of the fluorescence lifetime; the accuracy of the pollution component determination is greatly improved; and a reliable basis is provided for accurate management of water 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 unable to accurately determine pollution components. In actual detection process, natural light or other light sources in the environment can 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 are adopted to 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 further distinguishes and identifies various pollution components in the water sample by measuring the fluorescence lifetime, and generates a fluorescence lifetime image, the real-time background fluorescence calibration module monitors the environmental background fluorescence in real time, deducts the influence of the environmental background fluorescence on the measurement results, improves the measurement accuracy, the data processing and analysis module comprehensively processes and analyzes the obtained data, realizes qualitative and quantitative analysis of the pollution components and tracing, and the display and output and power module provides intuitive detection result display, 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 are adopted to 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 further distinguishes and identifies various pollution components in the water sample by measuring the fluorescence lifetime, and generates a fluorescence lifetime image, the real-time background fluorescence calibration module monitors the environmental background fluorescence in real time, deducts the influence of the environmental background fluorescence on the measurement results, improves the measurement accuracy, the data processing and analysis module comprehensively processes and analyzes the obtained data, realizes qualitative and quantitative analysis of the pollution components and tracing, and the display and output and power module provides intuitive detection result display, convenient data output mode and stable power support.

[0006] The sample collection and processing module collects a water sample from a water body to be measured, removes impurities through filtration, and dilutes the water sample according to a self-adaptive dilution multiple algorithm;

[0007] 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;

[0008] 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;

[0009] The real-time background fluorescence calibration module uses a high-precision ambient light sensor to monitor the environmental background fluorescence intensity in real time, and deducts the background influence from the total measured fluorescence intensity according to a dynamic background deduction algorithm;

[0010] 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;

[0011] Display and output module: equipped with high-resolution touch screen display to intuitively display test results and analysis reports, and provide various data output interfaces for data storage and sharing. It is powered by rechargeable battery and has functions of power monitoring and charging management.

[0012] Further, the sample collection and processing module dilutes the water sample according to the adaptive dilution multiple algorithm. Specifically, the dilution multiple is determined according to the estimated initial concentration of the water sample and the optimal detection concentration interval of the detection device . The calculation formula is: If , take If , take If the calculation result is not an integer, take the upper integer.

[0013] 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. The wavelengths of the excitation light can be adjusted according to different detection requirements. The fluorescence signals are detected and recorded by high-sensitivity fluorescence detectors, which 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 and emission wavelengths is obtained, and the measured fluorescence intensity is compensated by the fluorescence intensity dynamic compensation formula to form three-dimensional fluorescence spectrum data.

[0014] 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 , 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. and are obtained by real-time measurement of the temperature and humidity sensors. and are the reference environmental conditions for device calibration.

[0015] Further, the real-time fluorescence lifetime imaging module solves the fluorescence lifetime of each component according to a multi-component fluorescence lifetime separation algorithm formula, specifically, for multi-component fluorescent substances, the mixed fluorescence signal intensity changes with time may be expressed as: wherein, is measured by a time-correlated single photon counting detector, is the fluorescence lifetime of the first fluorescent substance, is the initial fluorescence intensity contribution of the first fluorescent substance, is the initial fluorescence intensity contribution of the first fluorescent substance, is the background noise intensity, which is estimated by measuring a non-fluorescent sample or data in the late stage of fluorescence signal decay, is the number of components of the fluorescent substances in the water sample, is the time in the fluorescence signal decay process, which is estimated according to the source and preliminary analysis of the water sample and is adjusted in the fitting process, the above formula is fitted by a non-linear least squares method to solve and , thereby accurately separating the fluorescence lifetime of each component, and generating a fluorescence lifetime image according to the measured fluorescence lifetime information. 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 and accurately removes the influence of the environmental background fluorescence from the measurement data through data processing and analysis.

[0016] 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

[0017] is obtained, the total measured fluorescence intensity changes with time is , the fluorescence intensity after background removal is , the dynamic background fluorescence intensity is calculated by , wherein is the total fluorescence intensity measurement and the background fluorescence calibration synchronization time point, thereby calculating the fluorescence intensity after background removal: wherein, is the size of the sliding window.

[0018] ​Furthermore, 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 then performs qualitative analysis of the pollutants using a comprehensive similarity algorithm. Specifically, the feature vector of the unknown water sample pollutant 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.

[0019] Compared with existing technologies, this three-dimensional fluorescence portable water quality analyzer for identifying and tracing pollutant components has the following advantages:

[0020] I. This invention acquires fluorescence intensity information of water samples at different excitation and emission wavelengths through a three-dimensional fluorescence detection module, forming rich three-dimensional fluorescence spectral data. It also introduces a real-time fluorescence lifetime imaging module to measure the fluorescence lifetime of fluorescent substances. By utilizing the principle that different fluorescent substances have different fluorescence lifetime characteristics, it can further distinguish and identify various pollutants in water samples. Through fluorescence lifetime measurement and imaging, these pollutants can be accurately distinguished, greatly improving the accuracy of pollutant identification and providing a reliable basis for the precise treatment of water pollution.

[0021] Secondly, the application provides important clues for the tracing of pollution components by comparative analysis of different water sample data, combined with information such as the types, contents and spatial distribution of pollution components, and meanwhile, the display and output and power module are equipped with high-resolution display screens, which can intuitively and clearly display detection results and analysis reports, support touch screen operation, facilitate user interaction and inquiry, and provide various data output interfaces, so that the detection results and analysis reports can be output to external devices, thereby facilitating data storage, sharing and further processing.

[0022] Additional advantages, objects, and features of the application will be set forth in part in the description which follows, and in part will become apparent to those having ordinary skill in the art upon examination of the following or can be learned from practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0024] Figure 1 It is a three-dimensional fluorescence portable water quality analyzer structure schematic diagram for pollution component determination and tracing;

[0025] Figure 2 It is a flow chart of a three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing. DETAILED DESCRIPTION

[0026] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined application purposes, the following will combine the drawings and the preferred embodiments to specifically describe the specific embodiments, structures, features and effects of the present application.

[0027] Embodiment one

[0028] 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.

[0029] The sample collection and processing module collects water samples at the upstream, midstream, downstream of the river and the vicinity of the possible sewage discharge outlet, respectively, 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 , through the analysis of the river water quality data and the surrounding enterprises to estimate the characteristics of the sewage, and the best detection concentration interval of the detection equipment Provided by the equipment manufacturer, according to the adaptive dilution multiple formula: , if , , if The calculation result is not an integer, and is rounded up, and the dilution multiple is calculated according to the formula , the water sample is appropriately diluted to prepare for subsequent detection.

[0030] The processed water sample is sent to 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 electrical signal. In the measurement process, environmental temperature, humidity and other factors will affect the fluorescence intensity. The temperature and humidity sensor monitors the temperature and humidity of the measurement environment in real time The temperature influence coefficient and the humidity influence coefficient are obtained by measuring a large number of standard fluorescent substances under different temperature and humidity conditions and fitting them by regression analysis and other methods. The temperature and humidity of the standard measurement environment are the reference environmental conditions for equipment calibration. According to the fluorescence intensity dynamic compensation formula , where is the actual measured fluorescence intensity, the formula is used to compensate , and accurate fluorescence intensity data is obtained and , are preliminarily determined based on experimental measurement and theory. Experimental measurement is the measurement of standard fluorescent substances under different temperature and humidity conditions and linear regression analysis. Theoretical calculation is estimated according to the physical and chemical properties of fluorescent substances combined with theoretical models. In practical application, the known concentration and characteristics of the actual water sample are measured and compared. If the compensated value is biased, adjust and according to the deviation direction and size.

[0031] The real-time fluorescence lifetime imaging module emits pulsed excitation light, so that the fluorescent substances in the water sample are excited. 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 the detector. The component number of the fluorescent substance in the water sample is estimated by measuring the data of the non-fluorescent sample or in the late stage of fluorescence signal decay First, an estimate is made based on the source of the water sample and preliminary analysis, such as considering the types of substances that may be emitted by surrounding enterprises. During the fitting process, adjustments are made by comparing the fitting effects under different component fractions, based on the multi-component fluorescence lifetime separation algorithm formula: The fluorescence lifetime of each component was calculated by fitting the above formula using the nonlinear least squares method. and initial fluorescence intensity contribution It generates fluorescence lifetime images, which visually show the distribution of fluorescence lifetime at different locations in the water sample.

[0032] 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 ambient light sensor's position at any given time. Measured background fluorescence intensity The dynamic background fluorescence intensity is first calculated using the sliding window averaging method through a dynamic background subtraction algorithm. : Then calculate the fluorescence intensity after background subtraction: ,in, To measure the total fluorescence intensity, The size of the sliding window was determined through experimental optimization. This algorithm accurately subtracts the influence of background fluorescence from the total measured fluorescence intensity, ensuring the accuracy of the measurement data.

[0033] The data processing and analysis module comprehensively processes the data acquired by the above modules. First, it performs qualitative analysis of pollutant components using a comprehensive similarity algorithm for pollutant components. Specifically, it sets the feature vector of the unknown water sample. It is extracted from the data processed by the previous modules, such as extracting feature values ​​like fluorescence intensity and fluorescence lifetime, and the feature vector of the known pollutant component standard sample. The weight vectors of each feature were obtained and stored in a database through the measurement and analysis of a large number of water samples containing known pollutants. There are two initial methods for determining the weights: one is to assess the importance of each feature based on practical experience and assign initial weights; the other is to perform principal component analysis on a large amount of measurement data to calculate the variance contribution rate of each feature as the initial weights, and then apply the formula: ,in, , Calculate the overall similarity This allows for a preliminary assessment of the potential pollutants in the water sample. Subsequently, quantitative analysis of these pollutants is performed, and their concentrations are predicted using a multiple linear regression model. Let the concentration of each pollutant be... Characteristic variables affecting concentration The regression coefficients are obtained from the results of data processing. By measuring a large number of standard water samples with known concentrations, the data pairs of characteristic variables and concentrations are obtained, and the least square 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. The preliminary coefficient can be obtained by fitting the least square method to minimize the error sum of squares of the predicted value and the actual value, 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 greater the The initial value may be larger. 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.

[0034] The display and output unit clearly displays the detection results and analysis report on the high-resolution display screen, including the types, contents and spatial distribution of the pollution components in the river, and other information. Environmental protection department staff can query related data in detail through touch screen operation, and output the detection results and analysis report to the computer through USB interface for further research and report writing.

[0035] Through the detection and analysis of water samples at different positions of the river, it is determined that the main pollution component in the river is a certain type of organic compound, and it is found that the concentration of the pollution component in the downstream water sample is significantly higher than that in the upstream, and the concentration of the pollution component in the water sample near the sewage outlet of a certain enterprise is extremely high. Combined with the results of comprehensive similarity analysis, it can be basically determined that the enterprise is the main source of river pollution.

[0036] Example two

[0037] A large drinking water source bears the task of supplying drinking water for millions of residents in surrounding cities. In order to ensure the safety of residents' drinking water, it is necessary to regularly monitor the water quality of the water source with high frequency and high precision, and timely discover potential pollution risks to ensure the quality and safety of residents' water.

[0038] According to the sampling plan, the sample collection and processing module of the water quality analyzer collects water samples at multiple key areas of the drinking water source, including but not limited to water intake, reservoir center, river confluence, and areas around possible pollution sources, etc. In order to ensure the representativeness of the collected water samples, sampling is also carried out at different depths (surface, middle layer, bottom layer). The collected water samples are first coarsely filtered to remove larger impurities such as branches, weeds, etc., and then finely filtered through a precision filter to remove small suspended solids and impurities. Subsequently, based on the estimated initial concentration of the water sample (comprehensively estimated by considering factors such as long-term historical monitoring data of the water source, surrounding industrial distribution, agricultural activities, and recent weather changes, etc.) and the optimal detection concentration range of the detection equipment, an adaptive dilution factor algorithm is used to accurately calculate the dilution factor, and the water sample is accurately diluted to ensure that the water sample concentration is within the optimal sensitivity range of the detection equipment.

[0039] 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. A 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, a temperature and humidity sensor monitors the temperature and humidity changes in the measurement environment in real time and accurately. The data processing system uses a fluorescence intensity dynamic compensation formula to consider the temperature influence coefficient, humidity influence coefficient, and the temperature and humidity of the current measurement environment and the standard measurement environment to finely calibrate and compensate the actual measured fluorescence intensity, thereby obtaining accurate and reliable fluorescence intensity data.

[0040] The real-time fluorescence lifetime imaging module emits stable and accurate pulsed excitation light to uniformly irradiate the water sample, so that the fluorescent substances in the water sample are fully excited. A time-correlated single-photon counting detector accurately measures the arrival time of fluorescent photons due to its high sensitivity and precise time resolution. By using a multi-component fluorescence lifetime separation algorithm, the change of mixed fluorescence signal intensity with time is deeply and carefully fitted and analyzed, not only accurately separating the fluorescence lifetime and initial fluorescence intensity contribution of each component, but also accurately calculating the relative content of each component, and generating high-resolution, clear and intuitive fluorescence lifetime images, which provides a strong visual basis for analysts to deeply understand the characteristics of fluorescent substances in the water sample.

[0041] The ambient light sensor always maintains a high sensitivity working state, and monitors the intensity and spectral characteristics of the environmental background fluorescence in real time and continuously. The real-time background fluorescence calibration module uses advanced dynamic background subtraction algorithms to analyze and process the data collected by the ambient light sensor in real time, accurately calculates the dynamic background fluorescence intensity using the sliding window average method, and accurately subtracts the influence of the background fluorescence from the total measured fluorescence intensity, thereby maximizing the authenticity and reliability of the measurement data.

[0042] The data processing and analysis module comprehensively and deeply processes the massive data obtained by the above-mentioned modules. First, the pollution component comprehensive similarity algorithm is used to compare the measured unknown water sample feature vector with the known feature vector of the 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 applications, and the comprehensive similarity is accurately calculated, so that the presence or absence of potential pollution components and the possible types of pollution components in the water sample can be accurately determined. Then, the pollution component concentration prediction formula is used to perform high-precision quantitative analysis on the possible pollution components based on multiple feature variables (such as fluorescence intensity and fluorescence lifetime) affecting the concentration and the regression coefficients estimated by the strict least squares method, and to accurately determine whether the concentration is within the safe range, thereby providing scientific and accurate data support for the comprehensive evaluation of water quality.

[0043] The display and output unit clearly displays the detailed and comprehensive detection results and analysis reports on the high-resolution display screen in an intuitive and easy-to-understand manner. The content includes the overall evaluation of water quality, the presence or absence 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 relevant 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, which facilitates further research, analysis, and management decision-making by professionals. In addition, the detection results and analysis reports can also be output to external storage devices through the USB interface, which is convenient for data backup and offline analysis.

[0044] After comprehensive and detailed detection and analysis of the water samples in the drinking water source, no obvious pollution components were found, and all indicators met the national drinking water standards.

[0045] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, 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, as long as the changes or modifications do not deviate from 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 measured, 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 multi-component fluorescence lifetime separation algorithm formula is used to fit and solve the fluorescence lifetime of each component to generate a fluorescence lifetime image, thereby distinguishing and identifying 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; Data processing and analysis module: the data of three-dimensional fluorescence detection, real-time fluorescence lifetime imaging and background fluorescence calibration module are comprehensively processed, the pollution component is qualitatively analyzed through a pollution component comprehensive similarity algorithm, specifically, the characteristic vector of an unknown water sample pollution component is , the characteristic vector of a known pollution component standard sample is , the weight vector of each characteristic is , the comprehensive similarity is , and the calculation formula is: , wherein , , is the characteristic vector of the unknown water sample pollution component, is the characteristic vector of the known pollution component standard sample, indicates the importance of the th characteristic in the similarity calculation, represents the number of characteristic dimensions participating in the pollution component qualitative analysis, and the pollution component quantitative analysis 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 pollution component quantitative analysis, and the pollution component quantitative analysis is carried out through a multiple linear regression model; A display, output and power module: a high-resolution touch screen display is provided to visually display the detection results and analysis report, and various data output interfaces are provided for 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 , take If , take the integer part of the calculation result.

3. The three-dimensional fluorescence portable water quality analyzer for pollution component determination and tracing 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, and detects and records these fluorescence signals. The wavelength of the excitation light can be adjusted according to different detection requirements. A high-sensitivity fluorescence detector is used to capture and convert the fluorescence signals into electrical signals, obtain the actual measured fluorescence intensity, and obtain the fluorescence intensity information of the water sample under different excitation wavelengths and emission wavelengths through multi-angle and multi-wavelength scanning detection. The measured fluorescence intensity is compensated according to the fluorescence intensity dynamic compensation formula to form 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. , the compensated fluorescence intensity is , the temperature influence coefficient is , the humidity influence coefficient is , the temperature and humidity of the current measurement environment are and , the temperature and humidity of the standard measurement environment are and , and the fluorescence intensity dynamic compensation formula is used: , wherein, and By measuring the standard fluorescent substance under different temperature and humidity conditions, the regression analysis method is used to fit and The temperature and humidity are measured in real time by a temperature and humidity sensor, and are the reference environmental conditions for equipment 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 calculates the fluorescence lifetime of each component based on a multi-component fluorescence lifetime separation algorithm formula. Specifically, for a multi-component fluorescent substance, the change in the intensity of its mixed fluorescence signal over time is calculated. It can be represented as: ,in, Measured by a time-correlated single-photon counting detector. It is the first Fluorescence lifetime of a fluorescent substance It is the first The contribution of the initial fluorescence intensity of the fluorescent substances. It is the background noise intensity, estimated by measuring data from non-fluorescent samples or in the later stages of fluorescence signal decay. It represents the number of fluorescent substances in the water sample. This refers to the time during the fluorescence signal decay process, which is estimated based on the source of the water sample and preliminary analysis. Adjustments are made during the fitting process, and the above formula is fitted using the nonlinear least squares method to solve for the... and This allows for the accurate separation of the fluorescence lifetimes of each component, and the generation of fluorescence lifetime images based on the measured fluorescence lifetime information.

6. The three-dimensional fluorescence portable water quality analyzer for determination of contaminant components and tracing of sources 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 fluorescence intensity after deducting the background 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 fluorescence intensity after deducting the background: wherein, is the size of the sliding window.

Images