161 results about "Fluorescence Spectrophotometry" 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.

Aspects of the present disclosure include methods for spectrally resolving light from fluorophores in a sample. Methods according to certain embodiments include detecting light with a light detection system from a sample having a plurality of fluorophores having overlapping fluorescence spectra and spectrally resolving light from each fluorophore in the sample with a generalized least squares algorithm. In some embodiments, methods include estimating the abundance of one or more of the fluorophores in the sample, such as on a particle. In certain instances, methods include identifying the particle in the sample based on the abundance of each fluorophore and sorting the particle. Methods according to some embodiments includes spectrally resolving the light from each fluorophore by calculating a spectral unmixing matrix for the fluorescence spectra of each fluorophore. Systems and integrated circuit devices (e.g., a field programmable gate array) for practicing the subject methods are also provided.

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 discloses a thermal detection system and a chiral substance identification method, and relates to the technical field of micro-nano optics, the thermal detection system and the chiral substance identification method, based on the structure of the thermal detection system and the steps of the chiral substance identification method, a chiral substance to be detected is configured into a corresponding solution to be detected; a solution to be detected is sampled and placed in the absorber, the surface plasmon effect generated when the metal resonance layer receives chiral light irradiation is utilized, a corresponding thermal signal is output, then the thermal signal is captured and analyzed through the thermal detection system, and high-precision identification of chiral substances is achieved. Compared with a traditional circular dichroism and circular polarization fluorescence spectrophotometer device, the technical scheme provided by the invention is simple in structure, convenient to operate and relatively low in requirements on the concentration and the volume of a detected sample.

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.

Provided are a coal testing system and method, and a storage medium. The system comprises: a detection unit, which is used for collecting spectral data of a coal sample under test; a training unit, which is used for constructing, by means of the spectral data, neural networks across neural network dimensions on the basis of a greedy search, and obtaining a coal sample test model by means of performing training on the basis of simulated samples which have been subjected to sample augmentation; and an analysis unit, which is used for executing fusion processing on the spectral data to obtain target spectral data, and on the basis of the coal sample test model, executing target spectral data inference to obtain a coal test result, wherein the detection unit comprises a near-infrared spectroscopy collection module and an X-ray fluorescence spectroscopy collection module.

This invention discloses a method for determining fiber microplastics in aqueous textile solutions based on fluorescence spectrophotometry, belonging to the field of textile pollutant detection technology. The method includes: S1, collecting wastewater and filtering it through a filter membrane; S2, rinsing the filter membrane with sodium hypochlorite solution; S3, rinsing the fiber microplastics on the filter membrane into a separatory funnel; S4, pouring out a portion of the fiber microplastics from the upper end of the separatory funnel and collecting another portion from the lower end; S5, repeating S1-S4, rinsing the filter membrane with hydrochloric acid during this process, and collecting the remaining fiber microplastics; S6, dyeing the three solutions obtained; S7, preparing standard series solutions using polyester, polyamide, and polypropylene standard liner; S8, measuring and plotting a standard curve of fluorescence intensity versus fiber microplastic concentration using a fluorescence spectrophotometer; S9, measuring the fluorescence intensity of the three solutions obtained in S6. This invention is applicable to the field of aqueous textile solutions, enabling quantitative analysis of unknown samples, and can analyze both single and mixed samples with minimal detection bias.

The invention provides a sea surface oil film thickness measuring method based on optimized laser-induced fluorescence spectrum wave bands, and belongs to the technical field of spectral analysis. The method comprises the following steps: emitting an excitation light beam to a to-be-measured sea surface oil film by using a laser, and exciting the oil film to generate a fluorescence signal; receiving the fluorescence signal based on a spectrum acquisition device, and obtaining fluorescence spectrum data of the oil film; selecting a characteristic wave band from the fluorescence spectrum data through a sparse partial least square model, and predicting the thickness of the sea surface oil film based on the characteristic wave band in combination with Lasso regression; meanwhile, the selection of characteristic wave bands is optimized by using a hedera helix algorithm. According to the method, the characteristic wave band of oil film detection is selected through the sparse partial least square model, the oil film measurement characteristic wave band is efficiently and accurately obtained, full-wave band collection is avoided, and the detection efficiency is improved; and in combination with the hedera helix optimized sparse partial least square model, the accuracy of characteristic wave band selection and the generalization of the model are further improved, and the precision and efficiency of oil film thickness measurement are remarkably improved.

A digital-physical twin system and method for environmental process modeling and forecasting are disclosed. The system includes a digital twin server configured to receive environmental data from a real-world environment, including hyperspectral and spectroscopic imaging, simulate environmental process transitions using a predictive model based on the environmental data, and generate parameters for a physical experiment designed to validate or refine the predictive model. A physical twin device, comprising a scaled and instrumented representation of the real-world environment, is configured to execute the physical experiment under controlled conditions. Experimental data is returned to the digital twin to iteratively refine the predictive model in a closed-loop learning cycle using self-supervised and reinforcement learning. The system supports spatially-spectrally selective experimentation, including fluorescence spectroscopy, to enhance environmental sensing. This architecture enables scalable, sample-efficient modeling of processes such as post-wildfire hydrology, vegetation regrowth, and soil change.

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 specifically discloses a method for determining the content of chromium, silicon, phosphorus and titanium in high-carbon ferrochrome, which adopts a melting sample preparation-X fluorescence spectrometry method for determination, and comprises the following steps: (1) sample preparation: uniformly mixing a sample with lithium hydroxide, boron oxide, strontium nitrate and other oxidants, covering with lithium tetraborate, setting a melting procedure, and determining the content of chromium, silicon, phosphorus and titanium in the high-carbon ferrochrome by controlling the heating rate, segmentally controlling the temperature and preserving the heat; the full-automatic completion of pre-oxidation and melting can be realized, and the homogeneous glass fuse piece meeting the analysis requirement is obtained; (2) preparing a calibration working curve sample: selecting various national standard samples to establish a calibration working curve; and (3) determining by using an X-ray fluorescence spectrophotometer. According to the method provided by the invention, a flux crucible does not need to be additionally prepared for early-stage sample treatment, complete sample melting is ensured, the platinum-yellow crucible is prevented from being etched, the homogeneous glass fuse piece meeting the analysis requirement is obtained, and the precision and the accuracy of the result both meet the use requirement.

The invention provides a copper concentrate sample traceability method based on X-ray fluorescence spectrum and isotope detection, and relates to the technical field of copper concentrate traceability. Data sampling is carried out on subjective factors and objective factors in the copper concentrate sample sampling process, data storage is carried out based on a block chain to improve the safety and accuracy of data, discretization, standardization, abnormal value correction and principal component analysis processing are carried out on the data analysis result of the copper concentrate sample, and therefore data standardization is guaranteed, and the accuracy of the data analysis result is improved. Based on a first mining area feature fingerprint database set obtained through historical data mining, determining a target mining area to which the copper concentrate sample belongs and a corresponding first similarity; by means of the technical scheme, standardization processing of the copper concentrate analysis result can be achieved, then the consistency rule is extracted, the confidence probability is given out for the traceability result in combination with the sampling process data, and therefore the obtained traceability result is more accurate.

The invention relates to a gallium oxide defect detection method. The method comprises the following steps: step 1, obtaining exciting light with a proper wavelength; 2, modulating the exciting light obtained in the step 1 so as to enable the exciting light to accurately enter a microscope system with proper energy; 3, irradiating the modulated exciting light to a gallium oxide sample on an electric displacement table through a microscope system, collecting fluorescence generated after the gallium oxide sample is excited through the microscope system, and transmitting the fluorescence to a spectrograph system to obtain a corresponding fluorescence spectrogram under a preset single pixel point position; and 4, setting a spectrograph system to collect the fluorescence intensity under a specific wavelength, and driving the gallium oxide sample to move through an electric displacement table so as to scan the fluorescence intensity of all pixel point positions in a sample detection range, thereby obtaining a gallium oxide defect fluorescence intensity imaging graph in the sample detection range. The method has the advantage of high sensitivity, can realize rapid nondestructive detection, and also reduces the detection cost at the same time.

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.

The invention discloses an iron ore composition detection method and system based on machine learning, and relates to the technical field of data processing.The method comprises the steps that iron ore feature information of target iron ore to be detected is collected, and a plurality of iron ore samples are collected; performing drying and grinding parameter optimization according to the iron ore characteristic information, drying and grinding the plurality of iron ore samples, and collecting the particle size and mass in each drying and grinding process to obtain a plurality of particle size sequence sets and a plurality of mass sequences; preparing a plurality of detection samples, and performing sample quality analysis according to the optimized drying and grinding parameters, the plurality of particle size sequence sets and the plurality of quality sequences to obtain a plurality of sample quality coefficients; and carrying out X-ray fluorescence spectrum detection on the plurality of detection samples to obtain a plurality of spectrum detection results, and carrying out component identification on the plurality of spectrum detection results according to the plurality of sample mass coefficients to obtain an iron ore component detection result. The technical problem of poor iron ore component detection accuracy in the prior art is solved.

The invention belongs to the field of soil dissolved organic matter analysis, and provides a multispectral-based DOM detection and reclamation influence evaluation method, which comprises the following steps: step 1, collecting dry farmland soil samples of different reclamation years, and obtaining soil column samples of a plough layer, a plow pan and subsoil; 2, extracting, centrifuging and filtering the soil sample to obtain a DOM solution; 3, detecting the DOM solution by adopting an ultraviolet-visible absorption spectrum; step 4, adopting a three-dimensional fluorescence spectrum and combining parallel factor analysis to obtain fluorescence components and source characteristics of the DOM solution; step 5, analyzing molecular composition and characteristic parameters of the DOM solution by adopting solid-phase extraction in combination with Fourier transform ion cyclotron resonance mass spectrometry; and step 6, based on the detection data in the steps 3-5, evaluating the influence of reclamation years on the composition, structure and degradation characteristics of the DOM. According to the method, multi-dimensional detection of soil DOM is realized through a multi-spectrum and mass spectrum combined technology, and DOM is comprehensively analyzed from a macrostructure to molecular composition.

In general, in one aspect, the invention features a method of fluorescence spectroscopy including providing a high-performance sensor that combines imaging with high intrinsic time resolution and high

Provided is a phosphor powder in which the balance of suitability, brightness, and excitation light blocking properties of a complex obtained from the phosphor powder with respect to a small-sized light-emitting device is improved. A phosphor powder containing SCASN phosphor particles, the phosphor powder having a volume-based median diameter (D50) of 0.1 [mu] m to 5.0 [mu] m (inclusive) as determined by a laser diffraction scattering method, and a peak wavelength of a fluorescence spectrum measured by a spectrophotometer when the phosphor powder is irradiated with light having a wavelength of 455 nm of 590.0 nm to 630.0 nm (inclusive), the absorption rate when the phosphor powder is irradiated with light having a wavelength of 455 nm is 80.0% or more.

The application discloses a kind of full-automatic high-throughput space-time resolution fluorescence spectrum imaging system and method, it is related to fluorescence signal spectrum field, including: workbench, sample stage, objective, for preloading sample stage with sample and placing it on workbench on mechanical arm sample inlet module, for laser beam to the output module of picosecond pulse laser of objective, for simultaneously collecting the spectral data and dynamic data of fluorescence signal generated after sample is focused by laser beam fluorescence signal detection module and control module;Sample stage and objective are sequentially spaced apart on workbench along the vertical direction from top to bottom;Mechanical arm sample inlet module, picosecond pulse laser output module and fluorescence signal detection module are respectively connected with control module communication.This application can realize the simultaneous acquisition of spectral data and dynamic data of fluorescence signal automatically.

The invention discloses a boric acid group iridium complex probe as well as a preparation method and application thereof, and relates to the technical field of analytical chemistry. The boric acid group iridium complex probe is formed by complexing # imgabs0 # precursors and PIPB ligands with boric acid groups, targeted recognition of polyphenol substances can be achieved, and quantitative and qualitative detection of the polyphenol substances is achieved through fluorescence spectrophotometry. Besides, the boric acid group iridium complex probe provided by the invention has the characteristic of long service life, can realize targeted noise reduction detection of polyphenol substances through a time-resolved emission spectrum under the condition of high interference intensity, and has extremely high sensitivity; the technical scheme provided by the invention can be applied to accurate detection of polyphenols in fruits.

Multivariate machine learning (ML) techniques can be applied to an XRF spectra and mitigate matrix effects and enable simultaneous quantification of composition, even when markers elements or ions of interest are imperceptible in the XRF spectra. Physical (e.g., density) and chemical (e.g., total dissolved solids and hardness) properties of the material can be also quantified using ML techniques.

This invention discloses a method for quantitative analysis of multiple components in oxidized slag based on X-ray fluorescence spectroscopy, belonging to the field of industrial process detection technology. The method includes: acquiring the raw energy spectrum data of a standard oxidized slag sample and the oxidized slag sample to be tested, and performing background subtraction and smoothing noise reduction; extracting the integral intensity of the characteristic peaks of target elements, establishing spectral interference correction relationships and matrix effect compensation relationships; establishing regression prediction models and residual compensation models for each target oxide based on the compensated characteristic intensities; inputting the characteristics of the sample to be tested into the models, and outputting the final predicted values ​​of each target oxide; improving the accuracy of feature information extraction in the multi-component system of oxidized slag, reducing errors caused by spectral overlap, excitation effects, and matrix effects, and improving the accuracy, result stability, and prediction consistency of quantitative analysis of multiple target oxides under different sample conditions, making it suitable for rapid detection and analysis of complex oxidized slag samples.

The invention discloses a sulfur-nitrogen co-doped carbon quantum dot modified polyaspartic acid derivative as well as a preparation method and application thereof. The derivative is prepared by taking citric acid and L-cysteine as precursors, synthesizing sulfur-nitrogen co-doped carbon quantum dots (SN-CDs) with rich functional groups on the surface by adopting a hydrothermal method, and introducing the sulfur-nitrogen co-doped carbon quantum dots into a side chain of polyaspartic acid (PASP) through graft copolymerization. The derivative not only retains the complexing ability of polyaspartic acid with metal ions such as calcium and magnesium, but also has excellent scale and corrosion inhibition performance; the optical characteristics of the carbon quantum dots are inherited, and stable fluorescence can be emitted under the excitation of specific wavelength, so that in-situ and real-time concentration monitoring in an industrial circulating cooling water system by utilizing a fluorescence spectrum technology is supported. The product does not contain phosphorus, is environment-friendly, conforms to the development trend of a green water treatment technology, and provides an innovative material solution for intelligent monitoring and fine management of a circulating water system while improving the comprehensive performance of scale and corrosion inhibition.

The present invention relates to methods for the fluorescence spectroscopic determination of the lignin content of cellulose samples, in which the lignin content is determined either by comparing the fluorescence emission spectrum of the sample with a reference sample or via the fluorescence decay spectrum. The present invention further relates to methods for the delignification of lignocellulose, particularly in the form of wood, in which such methods are used to monitor the progress of delignification, in particular to methods in which cellulose and lignin from the lignocellulose are separated from one another by extraction with an ionic liquid.

The invention discloses a method for simulating phosphorus and chromium migration during farmland irrigation with acid mine wastewater, which comprises the following steps: mixing a plant-derived organic material with deionized water to obtain a soluble organic matter; h2O2 oxidizes Fe < 2 + > to prepare pure Schwertmannite, and the pure Schwertmannite is placed in a phosphate solution to obtain phosphorus-loaded Schwertmannite; mixing the phosphorus-loaded Schwertmannite and the soluble organic matter with a chromate solution, carrying out oscillation adsorption, carrying out solid-liquid separation after adsorption, carrying out CrO and POconcentration change test on filtrate, and carrying out mineral characterization on separated solids; a three-dimensional fluorescence spectrum is adopted to track composition conversion of the soluble organic matter in the reaction process; and analyzing the component change of the supernate before and after the reaction by adopting Fourier transform ion cyclotron resonance mass spectrometry. The influence mechanism of DOM on phosphorus and chromium fate in mineral / water interface molecular fractionation is disclosed from the molecular level, and a scientific basis is provided for collaborative migration risk assessment of phosphorus and heavy metal in acid mine wastewater irrigation area farmland.

Described herein are various embodiments for the detection of ocular drugs, biomarkers, and small molecules using DNA or RNA aptamers. The DNA or RNA aptamer consists of a binding sequence to selectively and strongly bind to a compound of interest and can be linked to a readily detectable tag. The tag may be fluorescent, radioactive, or chromophore. The detection of the compound of interest can then be accomplished using a simple standard detection method, such as UV-Vis or fluorescence spectrophotometry, or a more complex method, such as mass spectrometry or electrochemical detection, preferably fluorescence detection or radioactivity detection with high sensitivity.

The invention discloses an automatic assembly line energy dispersion X-ray fluorescence spectrum array type scanning analysis method which comprises the following steps: a left automatic sample injection connection device / a right automatic sample injection connection device passes through a first conveying mechanism and a second conveying mechanism which correspond to each other; the array sample is sent to a sample conveying, positioning and detecting mechanism in the X-ray fluorescence spectrum array type scanning analysis device, and a Z-axis energy dispersion X-ray fluorescence spectrophotometer efficient double-light-path system above the X-ray fluorescence spectrum array type scanning analysis device carries out array detection analysis on the array sample; products are conveyed to the X fluorescence spectrum array type scanning analysis device in the middle through the left and right automatic sample injection connection devices, and array type detection is carried out, so that a high-efficiency and high-performance light path system is realized, the test requirements of different products are met, and the requirements of accuracy and efficiency in the test process can be met at the same time.

The invention discloses an X-ray fluorescence spectrum detection method of metal manganese, which comprises the following specific steps: step 1, pre-oxidizing a series of standard samples of metal manganese and a sample to be detected, and melting at high temperature to prepare a uniform and smooth glass sheet; 2, measuring the X-ray fluorescence intensity of the to-be-measured element in the glass sheet prepared in the step 1 by using an X-ray fluorescence spectrometer, drawing a calibration curve of the to-be-measured element according to the X-ray fluorescence intensity of the to-be-measured element and the certificate value of the element in the standard sample, and calculating the X-ray fluorescence intensity of the to-be-measured element according to the calibration curve obtained in the step 2. And calculating the mass fractions of manganese, silicon, phosphorus, iron and other components in the metal manganese sample. The method comprises the following steps: dissolving, oxidizing and evaporating a manganese metal sample by using a dilute nitric acid solution, melting lithium tetraborate as a flux and cobalt as an internal standard element of manganese at high temperature by using a high-frequency melting furnace, and melting the sample and lithium tetraborate into a flat and smooth glass sample wafer, so that the glass sample wafer meets the analysis requirements of an X-fluorescence spectrophotometer and does not damage a platinum crucible.

The invention provides a method for detecting the grafting rate of anion exchange resin, which is characterized by comprising the following steps: tabletting treatment: applying first pressure to a resin sample containing anion exchange resin, the pressure value of the first pressure being 15-45MPa, and thus preparing a tabletting sample; and grafting rate detection: carrying out X-ray fluorescence spectrum test on the tabletting sample, determining the content of characteristic elements in the tabletting sample, and calculating the grafting rate of the anion exchange resin based on the content of the characteristic elements. The characteristic elements are selected from at least one of elements contained in the anion exchange resin and elements introduced into the anion exchange resin after the anion exchange resin is pretreated. According to the scheme, on the basis of XRF detection, a certain pressure is applied to the resin sample before detection, the resin sample is tableted, and the obtained tableted sample is used for XRF detection, so that the accuracy of anion exchange resin grafting rate detection is improved to a great extent.

The present application relates to a perovskite test device and a battery production system. The perovskite test device comprises a box body (100), an object placement platform (200), a first test mechanism (300) and a second test mechanism (400); the object placement platform (200) is arranged in the box body (100) and is used for placement of a sample; the first test mechanism (300) is used for emitting first test light, and acquiring the fluorescence spectrum of the first test light passing through the sample; the second test mechanism (400) is used for emitting second test light, and acquiring absorption and scattering spectra of the second test light passing through the sample. The battery production system comprises the perovskite test device. With regard to the perovskite test device and the battery production system, the test device meets different spectral test requirements, simplified design of the overall structure of the test device is facilitated, and the space utilization rate of the test device is optimized.