209 results about "Three dimensional fluorescence" patented technology

The invention provides a lake water chemical oxygen demand internal and external source pollution quantitative tracing method and system, and relates to the technical field of pollution quantitative tracing. The method comprises the following steps: performing three-dimensional fluorescence spectrum analysis on water samples at different point positions of a lake to obtain fluorescence excitation / emission matrix spectrum EEMS data; performing parallel factor analysis on the EEMS data, identifying and classifying the fluorescent components of the dissolved organic matter DOM, and determining the type characteristics of each component; based on the maximum fluorescence intensity and the corresponding COD value of the fluorescence component, establishing a standardized multiple linear regression equation by adopting ridge regression analysis, and calculating the contribution percentage of each fluorescence component to the COD of the lake water body; analyzing influence paths of potential variables on DOM migration and transformation, and quantifying direct contributions and indirect contributions of different pollution sources to each fluorescent component through path coefficients; and calculating the total contribution of lake-entering rivers, bottom mud release and phytoplankton to the COD of the lake water body.

The invention discloses a TSFS sample generation method based on an improved generative adversarial network. The TSFS sample generation method comprises the following steps: step 1, acquiring TSFS data of a sample by using a three-dimensional fluorescence spectrometer; step 2, constructing a CA-WGAN-GP optimization model with a convolution attention mechanism, and performing data enhancement on an original TSFS sample; step 3, in a model training stage, storing generated data once after epoch training for a certain number of times, and enabling a generated sample coverage to have higher diversity by utilizing generator models of a plurality of training stages; 4, extracting enhanced sample features by using a pre-trained CNN model, projecting the sample features by using linear discriminant analysis LDA, and preliminarily screening samples according to a Mahalanobis distance and a set threshold value; and 5, performing secondary screening by using a K-means algorithm to obtain a final training sample set. According to the method, the time-consuming and labor-consuming problem of TSFS sample acquisition is effectively solved, the model over-fitting phenomenon is reduced, and the robustness of unknown data is improved.

The invention discloses a method and a system for analyzing a pollution source of a rainwater pipe network. The method comprises the following steps of: 1, obtaining a first key fluorescence characteristic parameter combination according to basic physicochemical indexes by adopting a fluorescence characteristic parameter prediction model; 2, three-dimensional fluorescence characteristic parameters of the pollution source are obtained, and a pollution source three-dimensional fluorescence characteristic data set is obtained; screening by adopting a multivariate statistical method to obtain a second key fluorescence characteristic parameter combination; 3, determining a fluorescence characteristic parameter combination according to the first key fluorescence characteristic parameter combination and the second key fluorescence characteristic parameter combination; 4, inputting the fluorescence characteristic parameter combination into the Bayesian mixture model to obtain the contribution rate of the pollution source to the receptor water quality, and completing the analysis of the pollution source of the rainwater pipe network; according to the method, the DOM fluorescent fingerprint information is predicted by adopting basic data; and based on the three-dimensional fluorescence characteristic parameters and in combination with a Bayesian mixture model, precise quantitative analysis of the pipe network pollution source is realized.

The invention provides a fluorescence-magnetic particle image fusion method which can be applied to the technical field of medical image processing. The method comprises the following steps: performing two-dimensional convolution processing on a registered two-dimensional near-infrared fluorescence image to obtain a multi-channel near-infrared fluorescence extended feature map, and performing initial fusion on the multi-channel near-infrared fluorescence extended feature map and a registered three-dimensional magnetic particle cross-sectional image to obtain a three-dimensional near-infrared fluorescence extended feature map; performing multi-round three-dimensional convolution processing on the three-dimensional near-infrared fluorescence extended feature map to obtain a multi-scale near-infrared fluorescence feature map, and performing multi-round three-dimensional convolution processing on the registered three-dimensional magnetic particle cross-sectional image to obtain a multi-scale magnetic particle feature map; and based on an adaptive cross attention mechanism, performing multi-round feature map fusion on the multi-scale near-infrared fluorescence feature map and the multi-scale magnetic particle feature map on the same scale, and performing filtering convolution processing on a multi-round feature map fusion result to obtain a three-dimensional fluorescence-magnetic particle fusion image.

The invention belongs to the technical field of river and lake water quality monitoring, and discloses a river and lake water quality intelligent traceability monitoring system and method.Dissolved organic matter fluorescent fingerprints are analyzed in real time through a three-dimensional fluorescent monitoring unit, pollution markers are detected, and parameters such as COD, ammonia nitrogen and total phosphorus are synchronously detected through a full-spectrum monitoring unit; the video monitoring unit is used for collecting section images / videos of rivers and lakes, other sensors are used for collecting real-time values of chlorophyll, pH, conductivity, turbidity and dissolved oxygen in a water body, then the data processing module is used for carrying out normalization processing on multi-source data, and the analysis and early warning module is used for analyzing water quality early warning scores, spectrum early warning scores and video early warning scores. All scores are synthesized to obtain a comprehensive early warning score, traceability is started when comprehensive early warning is larger than or equal to the grade II, pollution sources are recognized based on three-dimensional fluorescence spectrum comparison and upstream patrol, and a river and lake water body monitoring-early warning-traceability-verification closed loop is achieved.

The invention particularly relates to a water pollution intelligent traceability system based on a three-dimensional fluorescence spectrum, which relates to the technical field of environmental monitoring, and comprises a water sample collection and three-dimensional fluorescence data acquisition module, a data preprocessing and PARAFAC component decomposition module, a multi-source pollution characteristic fingerprint database module and an intelligent comparison and pollution source analysis module. According to the method, standard acquisition and preprocessing are adopted, and the original data quality is ensured by means of scattering rejection, instrument correction and the like; pure fluorescence components are decomposed through a PARAFAC algorithm, and feature extraction reliability is guaranteed through triple verification. In the comparison link, spectrum similarity, concentration proportion difference and space-time hydrological constraint multi-round screening are adopted, and irrelevant pollution sources are removed; and then the contribution proportion is quantified, and Monte Carlo simulation, water quality and specific pollutant cross validation are carried out, so that the crossing from suspected tracing to quantitative responsibility investigation is realized.

The invention belongs to the technical field of environmental monitoring, and particularly relates to a super-resolution fluorescence imaging analysis method based on hypersensitive fluorescent quantum dots. The quantum dots have high water solubility and stability, and can emit narrow-bandwidth fluorescence due to unique optical properties of the quantum dots. According to the invention, a quantum dot luminescent material is adopted to construct an ultra-high resolution microscope system which can be used for observing composite behaviors between micropollutants and quantum dots on a microscopic scale, and a three-dimensional fluorescence microspectrometer and a computer vision algorithm are integrated; the whole reaction process is deduced according to the evolution of the three-dimensional fluorescence spectrum between the micro-pollutants and the quantum dots in different space (concentration), time (reaction process) and chemical dimensions, and a multi-dimensional fingerprint spectrum is formed according to the whole reaction process and is used for identifying and tracing the micro-pollutants. The method has the advantages of being high in detection speed, high in fingerprint performance and less in interference of background factors.

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.

The invention relates to the technical field of municipal engineering, and provides a sewage pipeline low-pollution water inflow and infiltration diagnosis method based on a fluorescence spectrum image, and the method comprises the steps: collecting different types of sewage and different types of low-pollution water in a sewage pipeline troubleshooting region, and according to the mixing condition of the sewage and the low-pollution water in the sewage pipeline troubleshooting region, determining whether the sewage and the low-pollution water are mixed or not; the collected different types of sewage and different types of low-pollution water are mixed according to different proportions, a three-dimensional fluorescence spectrophotometer is used for detecting a mixed water sample, a fluorescence spectrum image corresponding to the mixed water sample is obtained, and according to the fluorescence spectrum image corresponding to the mixed water sample, the sewage type and proportion and the low-pollution water type and proportion, the low-pollution water is detected. And training the water sample type diagnosis model and the water sample type proportion diagnosis model, and performing low-pollution water inflow and infiltration diagnosis on the sewage pipeline to be diagnosed based on the models. In this way, low-pollution water inflow and infiltration diagnosis can be achieved when multiple types of sewage coexist in a sewage pipeline.

The invention relates to the technical field of electronics, and discloses a drainage pipe network pollutant tracing method, device and equipment, a medium and a program product. According to the method, the map similarity between a first three-dimensional fluorescence spectrum map corresponding to a first water sample of a target node and a second three-dimensional fluorescence spectrum map corresponding to each upstream pipe network node is calculated; and determining at least one target upstream pipe network node in the plurality of upstream pipe network nodes based on the map similarity, and determining pollution source information of abnormal water in a target node according to first water quality data of the target upstream pipe network node and second water quality data on a sewage flowing path between the target upstream pipe network node and the target node, the advantages of high sensitivity, rapid detection and the like of the three-dimensional fluorescence spectrum technology are utilized in the pollutant traceability process, and efficient and accurate traceability of pipe network pollutants is achieved.

The invention discloses a water sample pollution traceability analysis method fusing absorption-three-dimensional fluorescence spectrum characteristics, and relates to the field of water sample spectrum analysis traceability. According to the method, high-precision prediction of pollutant indexes is realized by utilizing multi-dimensional information of a three-dimensional fluorescence spectrum and an absorption spectrum of a water sample, qualitative and quantitative traceability of main pollution components and potential emission sources in a water body is carried out based on correlation analysis of the prediction indexes, a pollutant feature library and an emission source database, and the method has the advantages of high accuracy and high accuracy. The integration of water quality monitoring and pollution source management is realized, and a systematic and real-time technical means is provided for pollution analysis of a complex water body.

The invention discloses a three-dimensional fluorescence dynamic monitoring and automatic processing system for water quality. The system comprises a water sample collection module, a three-dimensional fluorescence spectrum detection module, a pollution fingerprint database, a spectral analysis unit, a diffusion path simulation module based on a distributed sensor network and an automatic control execution module. The diffusion path simulation module is used for acquiring spatio-temporal data through a water quality spectrum sensor, a hydrological sensor and a meteorological sensor, and dynamically predicting a pollutant migration track by combining a water body flow field model constructed by a finite volume method and a first-order dynamic fluorescence attenuation model; the automatic control execution module is based on the pollution recognition result and track prediction, emergency operations such as gate opening and closing and medicament adding are linked through a fuzzy logic algorithm, and full-process automation from monitoring to disposal is achieved. The system completes pollution identification within 10 minutes through a spectral angle mapping algorithm, and the defects that a traditional method lags in response and lacks dynamic prediction and automatic disposal are overcome.

The invention provides a drug screening and curative effect evaluation method and system based on a glioma organ-like model, and relates to the technical field of biological material analys.The method includes the steps that a three-dimensional fluorescence image of the glioma organ-like model is collected, signal intensity analysis and compensation processing are carried out, a growth feature mapping model is constructed, and the three-dimensional fluorescence image of the glioma organ-like model is obtained; and phenotypic characteristics for representing the glioma organoid heterogeneity are obtained. Inputting the phenotypic characteristics into a drug response evaluation network, and calculating a drug sensitivity score; the drug molecular feature library and the drug collaborative analysis model are combined, the synergistic interaction index of different drug combinations is calculated, the optimal drug combination is screened, the drug administration dosage and the drug administration time sequence are determined in combination with phenotypic features, and finally an individualized treatment scheme is generated. According to the invention, the curative effect of the drug on the glioma organs can be effectively evaluated, and the optimal drug combination and administration scheme can be screened out, so that the accuracy and effectiveness of glioma treatment are improved.

The invention relates to the field of environmental monitoring, and particularly discloses a non-negative matrix factorization and adaptive peak recognition fluorescence feature extraction and traceability system, which comprises a spectral data preprocessing module, a spectral data non-negative matrix factorization module, a component number automatic selection module, an adaptive peak recognition module, a feature library construction module and a similarity comparison module. An improved non-negative matrix factorization model is adopted to decompose the three-dimensional fluorescence spectrum matrix of a single sample, and an optimal component number K is automatically determined through multiplicative update rule iterative optimization; the self-adaptive peak identification module carries out selective filtering, accurately extracts the position and intensity of a fluorescence peak through multiple mechanisms, and carries out peak position calibration in a neighborhood; the Hungary algorithm is adopted to carry out characteristic peak matching to calculate the comprehensive similarity between the samples, and rapid and accurate identification of the pollution source is realized. The method has the advantages of high resolution, strong anti-interference capability, low requirement on the number of samples, automation and the like, and is suitable for water quality fingerprint feature extraction of a water sample in a complex environment and real-time source tracing of sewage.

The invention belongs to the technical field of regional water environment supervision, and discloses an industrial water pollution traceability method based on a convolutional neural network and water quality fluorescence fingerprints, and the method comprises the steps: obtaining wastewater water quality fluorescence fingerprint information based on a three-dimensional fluorescence spectrum technology, and constructing a CNN pollution traceability classification model by using three-dimensional fluorescence spectrum data as input; and outputting the category of the sample, and inputting the three-dimensional fluorescence spectrum data of the unknown sample into the trained CNN pollution traceability classification model to obtain a suspected pollution source. The industrial water pollution tracing method based on the convolutional neural network and the water quality fluorescent fingerprints is developed for industrial wastewater-urban sewage compound sewage treatment plants and industrial park sewage treatment plants, has the characteristics of simplicity and convenience in operation, low cost, high efficiency and good accuracy, has a relatively high practical application value, and has a wide application prospect. The standard-exceeding emission pollution source can be quickly identified, and technical support is provided for regional water environment supervision.

The invention provides an underground water environment monitoring system and method, and the method comprises the steps: carrying out the three-dimensional fluorescence spectrum full-wave band scanning of a known type of pollution source reference sample in a target monitoring region, and obtaining a three-dimensional fluorescence spectrum data set; performing characteristic analysis on the three-dimensional fluorescence spectrum data set to obtain fluorescence characteristic components, and determining a characteristic excitation wavelength corresponding to each fluorescence characteristic component; the classification contribution degree of each characteristic excitation wavelength is evaluated, and a characteristic excitation wavelength combination during source tracing of the pollution source is obtained through screening; performing fixed wavelength scanning on the to-be-detected underground water sample in the target monitoring area according to the characteristic excitation wavelength combination, and determining the initial type of the pollution source; and determining the relative contribution degree of the type of the pollution source of the to-be-detected underground water sample, simulating the migration trend of the pollution plume according to the underground water migration and diffusion model, and generating the position of the pollution source of the to-be-detected underground water sample. By adopting the scheme of the application, the pollution source of the underground water can be quickly identified and positioned at low cost.

The invention belongs to the technical field of water pollutant identification, and particularly relates to a water pollutant distinguishing method and system based on multi-source spectrum fusion. According to the method, ultraviolet visible spectrum data and three-dimensional fluorescence spectrum data are effectively integrated in a multi-source spectrum data fusion mode, so that the characteristic information of water pollutants is captured, stably appearing characteristic absorption wavebands can be positioned by utilizing the ultraviolet visible spectrum data, and the water pollutants can be accurately detected. The method comprises the following steps: identifying a characteristic sub-region capable of representing the fluorescence response characteristic of a pollutant through three-dimensional fluorescence spectrum data, in a characteristic extraction stage, performing first-order derivative operation on an ultraviolet visible spectrum to position an absorption peak position, calculating curvature distribution of a three-dimensional fluorescence spectrum to identify the characteristic sub-region, and when a fusion characteristic is generated, performing first-order derivative operation on the three-dimensional fluorescence spectrum to identify the characteristic sub-region; according to the method, the key operation parameters are subjected to grid search optimization, and the optimal key operation parameter combination is screened out by performing multiple rounds of iterative training and evaluation on a preset training set and a verification set, so that the recognition performance of the real-time collected water sample is improved.

The invention belongs to the technical field of environment monitoring, and particularly relates to a quantitative recognition method for contribution of autogenous source organic carbon of a surface water body. Based on the stable isotope ratio and the three-dimensional fluorescence spectrum, the water DOM source analysis method is constructed, the source and characteristics of DOM are comprehensively analyzed, and the characteristic information and contribution of autogenous source organic carbon are specifically recognized. The three-dimensional fluorescence spectrum has the advantages of being rapid in detection, small in sample use amount and the like, DOM sources can be rapidly and qualitatively identified, different DOM sources can be quantitatively calculated through stable isotope ratio analysis, and meanwhile the research area land utilization, hydrological water environment and water quality parameters are combined, so that the DOM sources can be rapidly and qualitatively identified. And the source and migration rule of the DOM in the water body can be determined more comprehensively. The quantitative identification method provided by the invention has the advantages of more comprehensive water DOM research, more complete identification system and more reliable traceability result.

The invention relates to the technical field of monitoring and tracing of sewage, in particular to an online sewage monitoring method based on a three-dimensional fluorescence spectrum. The method comprises the following steps: step 1, sampling sewage in the whole area; 2, measuring COD, ammonia nitrogen and TOC values of the sewage sample; 3, scanning the sewage sample by adopting a three-dimensional fluorescence spectrometer to obtain three-dimensional fluorescence spectrum data; 4, analyzing the obtained three-dimensional fluorescence spectrum data by adopting a parallel factor analysis method to obtain fluorescence components of the sewage sample; 5, establishing a fluorescence database; and 6, establishing a sewage identification model. According to the invention, rapid source tracing of the sewage is realized, and the sewage incoming condition can be rapidly monitored.

The invention discloses a blue-green algae type discrimination method based on a three-dimensional fluorescence spectrum. The method comprises the following steps: S0, obtaining a to-be-detected sample; the method comprises the following steps: S1, acquiring original three-dimensional fluorescence spectrum data; s2, preprocessing the original three-dimensional fluorescence spectrum data; rayleigh scattering and Raman scattering in the original three-dimensional fluorescence spectrum are removed, and smooth denoising is carried out on the original three-dimensional fluorescence spectrum; s3, spectral features are extracted based on a parallel factor-peak ratio method, and spectral feature vectors are obtained; and S4, carrying out missing value supplement and data standardization processing on the obtained spectral feature vectors, inputting the processed feature vectors into a trained LightGBM multi-classifier, outputting probabilities by a classification model, and selecting a category with the maximum probability. According to the method, the distribution mechanism of the blue-green algae fluorescent pigment is combined, and the fluorescent component characteristics and the relative content characteristics of the fluorescent components of the blue-green algae are comprehensively considered, so that the three-dimensional fluorescence spectrum information of the blue-green algae sample can be more comprehensively, completely and meticulously represented, and the variety discrimination of different blue-green algae with smaller difference is realized.

The invention discloses a method for detecting soil active organic carbon based on fluorescence spectrometry, and belongs to the technical field of soil detection. The method comprises the following steps: sequentially drying, sieving and grinding fresh soil to obtain a soil sample, and sequentially performing active organic carbon extraction, purification, decoloration and pH regulation on the soil sample to obtain a soil liquid to be detected. The method comprises the following steps: adding fluorescein into a soil liquid to be detected to form a soil internal standard detection liquid, obtaining a soil fluorescence spectrum through three-dimensional fluorescence spectrum scanning, carrying out background deduction and correction coefficient correction, and calculating the active organic carbon concentration of the soil by using tryptophan, tyrosine and SMP fluorescence concentration standard curves. According to the method, an internal standard method is combined with a fluorescence spectrum technology, and through multi-step sample pretreatment and spectrum correction, the detection accuracy and the anti-interference capability are improved, the active organic carbon concentration of the soil can be rapidly and accurately determined, and an effective means is provided for soil carbon cycle research and quality evaluation.

A modality for compressed light field measurement to capture 3D fluorescent signals at kilohertz volume rate, is described. This modality, termed Squeezed Light field Microscopy (SQLFM), acquires the light field with an array of rotated 2D sub-aperture images. An anamorphic relay system applies anisotropic scaling, effectively "squeezing" the image along one axis. This allows the camera sensor to detect the light field with a letterbox-shaped region of interest (ROI). Each squeezed sub-aperture image is complementary to the others, facilitating successful 3D reconstruction from compressed measurement while preserving the nominal FOV and spatial resolution. SQLFM can achieve over a fivefold increase in acquisition rate compared to traditional LFM.

The invention discloses a multi-element information acquisition and analysis system based on telemetering drifting buoys, and relates to the technical field of marine environment monitoring. A three-dimensional fluorescence spectrometer, a temperature-salinity-depth sensor, a positioning module and a miniature water sampler are carried on each telemetering drifting buoy; the system is used for collecting algae fluorescence spectrums, water quality parameters and position data in real time, inputting the data into a trained random forest model to output the red tide occurrence probability, triggering multi-level early warning in combination with a preset expert rule engine, linking air and shore-based equipment and a data storage system, and utilizing laboratory true value data obtained by a miniature water sampler to determine the red tide occurrence probability. And performing incremental training on the random forest model every day, thereby dynamically optimizing internal structure parameters of the model. The method effectively improves the prediction probability of the red tide.

The invention relates to a three-dimensional fluorescence spectrum image super-resolution reconstruction method for a water quality detection instrument, which is suitable for reconstructing a low-resolution and sparse three-dimensional fluorescence spectrum image collected by a portable water quality detection instrument into a high-resolution full spectrum. According to the method, an efficient super-resolution reconstruction network architecture composed of a feature extraction module, an up-sampling module and a trainable multi-Gaussian mixture point spread function is constructed. A joint loss function combining a reconstruction error and a degradation consistency error is designed, and a joint training strategy is adopted to synchronously optimize a network and PSF parameters, so that accurate reduction of a fluorescence peak shape structure and enhancement of spectrum authenticity are realized. The applicability and robustness of the portable water quality detection instrument based on the three-dimensional fluorescence spectrum in pollutant identification and analysis tasks are improved, and the portable water quality detection instrument is suitable for actual scenes such as intelligent water quality monitoring.

The invention relates to the technical field of fluorescence detection, in particular to a three-dimensional fluorescence detection correction method based on double light sources, and the correction method comprises the following steps: obtaining double light source optical parameters, sample cell geometric parameters and original fluorescence intensity data, the geometric parameters of the sample pool comprise the length, width, height, pool wall reflection coefficient and sample attenuation coefficient of the sample pool; and constructing a light intensity distribution model in a three-dimensional space of the sample cell based on the optical parameters of the double light sources and the geometric parameters of the sample cell. According to the invention, accurate characterization of the light intensity of any spatial point in the sample cell is realized, light intensity deviation caused by various factors is quantified from the source, personalized correction is carried out on each spatial point, the influence caused by optical path difference at different positions, light source fluctuation and element error is effectively offset, and the accuracy and accuracy of the detection result are improved. The consistency of detection values of standard substances with the same concentration in different areas of the sample pool is greatly improved, and the linearity of a standard curve is remarkably optimized.

The invention discloses a Maotai-flavor liquor process category and authenticity identification model construction method, an identification method, an identification device and equipment. The method comprises the following steps: acquiring data of liquor samples; preprocessing the sample data to obtain preprocessed sample data; the preprocessed sample data are input into an initial identification model constructed based on a graph neural network or a partial least square discrimination method, the initial identification model is trained, target identification models are obtained, and the target identification models comprise a gas chromatography identification model, an ion chromatography identification model and / or a three-dimensional fluorescence spectrum identification model. According to the method, multiple analysis technologies such as GC, IC and EEM and a chemometrics modeling analysis module are adopted, analysis results of different technologies are mutually verified, a target identification model with high prediction precision is constructed, and accurate identification of the process category and authenticity of the Maotai-flavor liquor is realized.

The present disclosure provides methods, systems, and devices for coregistering imaging data to form three-dimensional superimposed images of target such as a tumor or a surgical bed. A three-dimensional map can be generated by projecting infrared radiation at a target area, receiving reflected infrared radiation, and measuring depth of the target area. A three-dimensional white light image can be created from a captured two-dimensional white light image and the three-dimensional map. A three-dimensional fluorescence image can be created from a captured two-dimensional fluorescence image and the three-dimensional map. The three-dimensional white light image and the three-dimensional fluorescence image can be aligned using one or more fiducial markers to form a three-dimensional superimposed image. The superimposed image can be used to excise cancerous tissues, for example, breast tumors. Images can be in the form of videos.

The invention discloses an activated sludge fluorescence online detection device based on a flow cell, and relates to the field of activated sludge biomass detection.The activated sludge fluorescence online detection device comprises a fluorescence spectrophotometer and a fluorescence spectrophotometer sample table arranged on the fluorescence spectrophotometer, and the fluorescence spectrophotometer is connected with a processor through a cable; the fluorescence spectrophotometer sample table is connected with a sample cup through a guide pipe, activated sludge is arranged in the sample cup, and a peristaltic pump is arranged on the guide pipe; the activated sludge continuously flows through the fluorescence spectrophotometer sample table through the guide pipe for three-dimensional fluorescence detection through the peristaltic pump, sludge sedimentation in a traditional cuvette is avoided, measurement is simple and convenient, and on-line real-time monitoring of the activated sludge biomass can be achieved.

The invention belongs to the technical field of fluorescence spectrum collection, and particularly relates to a quasi-three-dimensional fluorescence spectrum collection method and spectrograph based on a software phase locking technology, and the method comprises the following steps: respectively modulating coprime modulation frequencies of a plurality of laser light sources with different wavelengths, and synchronously exciting the laser light sources to the surface of a sample; a fluorescence signal generated on the surface of the sample is received and processed by a linear array CCD detector to obtain a multi-wavelength spectral signal simultaneously containing background light, scattered light and fluorescence components; inputting the multi-wavelength spectral signal into a software phase-locked amplification system, introducing a Costas ring to the software phase-locked amplification system for real-time tracking and correction, and generating a synchronous reference signal consistent with the laser modulation frequency; inputting the synchronous reference signal into a software lock-in amplifier, and extracting a plurality of pure fluorescence spectrum components excited by specific-frequency laser; and synthesizing the plurality of pure fluorescence spectrum components to finally form a quasi-three-dimensional fluorescence spectrum.

The invention provides an urban rainwater pipe network mixed connection tracing method based on a pollution source fluorescence spectrum library in combination with machine learning. The method relates to the fields of numerous pollution sources around a pipe network, complex mixing and connecting conditions and the like. The method comprises the following steps: sampling through an inspection well to obtain a water sample; extracting an organic matter multi-dimensional characteristic matrix from the water sample by adopting technologies such as three-dimensional fluorescence spectroscopy (EEM) and the like; and carrying out fluorescence data analysis on the multi-dimensional characteristic matrix by using an NPLSDA (N-Way Partial Least Squares Discriminant Analysis) model, carrying out comparative analysis and identification, and determining the source of the pollution source. According to the technology, the specific source of mixed connection sewage of the rainwater pipe network can be quickly diagnosed through mixed connection rainwater well sampling analysis, and efficient and convenient decision support is provided for mixed connection transformation and traceability investigation of the urban rainwater pipe network.