292 results about "Reflection spectrum" patented technology

The invention provides a semiconductor epitaxial growth control method and system, a control device and a related product, and relates to the technical field of semiconductor detection.The semiconductor epitaxial growth control method comprises the steps that reflection spectrum data is obtained in real time and analyzed to obtain an optical feature set, then the optical feature set is input into an optical transmission model for iterative optimization, and a predicted growth rate is obtained; and comparing the predicted growth rate with the target growth rate, generating deviation information, and outputting a process adjustment control instruction, so that the main control system performs closed-loop correction on the process parameters in the next process period. According to the invention, the optical feature set can dynamically represent the influence of the interface transition layer on the reflection spectrum, so that the inversion precision and robustness of the real epitaxial structure state are improved; closed-loop correction is performed on the process parameters based on the predicted growth rate, so that the growth rate drift can be inhibited in time, the process disturbance can be adaptively compensated, the manual calibration and intervention requirements are reduced, and the production stability, repeatability and batch-to-batch consistency are improved.

The invention provides an all-dielectric film system structure with visible near-infrared low transmission vegetation simulation, intermediate infrared high reflection and microwave high transmission. The device sequentially comprises, from top to bottom, a visible near-infrared simulated vegetation layer which is composed of first to fourth dielectric layers and is configured to simulate vegetation reflection spectrum characteristics in a wave band of 380-2500 nm and has a low transmission characteristic; the intermediate infrared high-reflection layer is formed by alternately stacking a first dielectric layer and a third dielectric layer, and is configured to form high reflection in a wave band of 3-14 microns; and a substrate layer; the thickness of the whole film layer is far smaller than the microwave wavelength, so that the film system keeps high transmission in the microwave band. According to the invention, the amorphous InSb material with high loss characteristic in visible near-infrared light is introduced, so that the average transmissivity of 1500-2500 nm is reduced to 0.095 while high-precision simulation of the vegetation reflectivity spectrum is realized, thereby realizing simulation of low transmissivity of the wave band vegetation.

The invention discloses a PVC film coating uniformity detection method based on spectral analysis, and relates to the technical field of optical detection, and the method comprises the following steps: S001, adopting a controllable incident illumination system with a multi-angle rotation function to carry out continuous angle scanning on the surface of a PVC film, collecting reflection spectrum intensity data in a corresponding wave band range according to different incident angles, and generating a spectrum data matrix containing interference characteristics; and S002, carrying out continuous wavelet transform processing on the spectral data matrix, carrying out multi-scale local decomposition on a spectral response signal, extracting and separating a periodic interference characteristic signal, and obtaining a purified spectral matrix after interference reduction. According to the method, through multi-angle spectrum collection and interference feature stripping, accurate identification of a coating thickness abnormal area and combination of strength indexes, spraying parameters are regulated and controlled, a detection-compensation-reinspection closed-loop mechanism is constructed, interference misjudgment is effectively avoided, and the accuracy and regulation and control efficiency of uniformity detection of the PVC film coating are improved.

The invention provides a semiconductor epitaxial growth parameter inversion method, a semiconductor epitaxial growth parameter inversion system, a semiconductor epitaxial growth parameter detection device and a related product, and relates to the technical field of semiconductor detection. The gas phase transmittance of a detection light path is further obtained, quantitative compensation is carried out on the actually measured reflection spectrum in the semiconductor epitaxial growth process, the compensated target reflection spectrum is closer to the real optical response of a semiconductor epitaxial film, and therefore spectral shape distortion and system errors caused by gas phase absorption superposition are effectively weakened. And the accuracy and the stability of the inverted growth parameters are obviously improved. Furthermore, the quantitative compensation value can be adaptively updated according to the fluctuation of the working condition, the inversion deviation introduced by the drift of the working condition is reduced, the consistency and comparability of the process are improved, and more reliable end point control and parameter closed-loop optimization can be conveniently realized.

A thermal measurement system enables high-resolution sub-surface temperature monitoring during additive manufacturing processes through machine learning demodulation of chirped fiber Bragg grating (C-FBG) sensors. An optical sensing subsystem includes a C-FBG sensor that encodes spatial temperature information in wavelength for high-temperature operation. A neural network model transforms complex reflection spectra into spatial temperature profiles with micrometer-scale resolution, overcoming limitations of traditional demodulation methods. A calibration subsystem generates synchronized spectral and thermal imaging data for training the neural network using controlled thermal profiles. The system captures steep thermal gradients and rapid cooling rates during laser powder bed fusion operations. A fiber embedding technique maintains the sensor in a strain-free condition at controlled sub-surface depths. The integration of high-temperature C-FBG sensors with machine learning signal processing achieves significant improvement in spatial resolution compared to traditional fiber optic thermal measurement approaches.

The invention discloses a transformer winding temperature and strain double-parameter monitoring method, system and device and a medium, and relates to the technical field of transformer monitoring, and the method comprises the steps: arranging a temperature sensing unit and a strain sensing unit on an optical fiber; a first reflection spectrum signal and a second reflection spectrum signal of the transformer winding are obtained and demodulated, and a first temperature signal of the transformer winding and a mixed signal containing a second strain signal and a second temperature signal are obtained; and taking the first temperature signal as compensation, and decoupling the mixed signal to obtain a second strain signal of the transformer winding. The fiber bragg grating technology is adopted, a plurality of sensors are inscribed on one optical fiber, synchronous measurement of temperature and strain is achieved, and strain data are compensated through winding temperature changes. According to the invention, the defects that only a single physical quantity can be monitored and the strain measurement accuracy is influenced by the temperature in the prior art are overcome, and accurate, convenient and efficient monitoring of the temperature strain of the transformer winding is realized in combination with online monitoring software.

The invention provides a polishing end point detection method, chemical mechanical polishing equipment and a storage medium, and belongs to the field of chemical mechanical polishing. The method comprises the steps that a reflection spectrum of the surface of a wafer in the chemical mechanical polishing process is obtained; correcting the reflection spectrum by adopting a preset correction coefficient to obtain a corrected reflection spectrum; dividing the corrected reflection spectrum into a dark noise spectrum and a to-be-measured spectrum based on a comparison result of the corrected reflection spectrum and a corresponding threshold value; determining the reflectivity of the surface of the wafer based on the to-be-measured spectrum, the dark noise spectrum, the reference spectrum and a preset reference spectrum reflectivity; the wafer thickness is determined using the reflectivity of the wafer surface to detect a polishing endpoint based on the wafer thickness. The terminal point detection accuracy is improved.

The invention relates to the technical field of sensors, and discloses a decoupling method of a temperature and pressure sensor, and the sensor comprises an F-P resonant cavity and a pressure sensing diaphragm with a fiber bragg grating. The method comprises the following steps: S1, transmitting a wide spectrum signal to a sensor, and collecting a reflection spectrum of the sensor; s2, performing baseline correction and noise reduction processing on the reflection spectrum, and extracting characteristic parameters; s3, if the characteristic parameters exceed the preset range, failure early warning is carried out; establishing and substituting the characteristic parameters into a physical model, performing multi-parameter optimal estimation, and outputting temperature and static pressure; and S4, if the characteristic parameters exceed the preset range, failure early warning is carried out. In order to enable failure early warning to be more accurate, the scheme can be adjusted to monitor the characteristic parameters extracted in the step S2 in real time, and the scheme is not limited to fixed nodes. According to the invention, intrinsic decoupling is realized, the measurement precision, the decoupling efficiency and the intelligent degree are greatly improved, the practicability is high, meanwhile, the self-diagnosis function is realized, and the reliability is ensured.

The invention discloses an intelligent glass fiber reinforced plastic curing temperature control method and system in combination with visual detection, and relates to the field related to intelligent manufacturing, and the method comprises the steps: carrying out the collection of a morphological spectral image and an infrared thermogram of a glass fiber reinforced plastic curing surface through a multispectral visual detection sensor; establishing a multi-dimensional pixel matrix including surface texture, reflection spectrum and infrared temperature distribution; carrying out polymerization analysis on optical coherence and temperature distribution continuity, constructing a photo-thermal coupling consistency tensor, and adaptively generating a curing region partition map; calculating a temperature gradient vector field of each adjacent region, and constructing a control mapping function by taking a morphological response characteristic index as a weight parameter; and a differential heating instruction is configured to control the multi-point array heating unit to execute self-adaptive heating control. The technical problem that existing glass fiber reinforced plastic curing temperature control cannot comprehensively and accurately sense and dynamically adapt to complex changes of the curing process is solved, and the technical effect of intelligent, accurate and differential control over the glass fiber reinforced plastic curing temperature is achieved.

The invention provides a thin film thickness measuring method and device based on spectrum confocal. The method is applied to the technical field of high-precision measurement. The method comprises the following steps: respectively acquiring a first reflection spectrum signal and a second reflection spectrum signal aiming at a tested film; determining a thin film upper surface wavelength corresponding to the first peak value in the first reflection spectrum signal, and determining a thin film lower surface wavelength corresponding to the second peak value in the second reflection spectrum signal; calculating the position of the upper surface of the film and the position of the lower surface of the film according to the wavelength of the upper surface of the film, the wavelength of the lower surface of the film and a pre-constructed wavelength-displacement model; and calculating the thickness of the thin film according to the upper surface position and the lower surface position of the thin film. According to the invention, accurate identification and extraction of peak value centers of the first peak and the second peak are realized, and the accuracy of thickness measurement is improved.

The invention provides a nondestructive identification method for a licorice producing area and a cultivation type based on a near infrared spectrum and deep learning, and the method comprises the steps: collecting the reflection spectrum data of a licorice sample, and carrying out the parallel enhancement processing through a plurality of enhancement methods; constructing a lossless identification model of the producing area and the cultivation type of the liquorice, wherein the lossless identification model performs lossless identification of the producing area and the cultivation type of the liquorice by adopting a multi-branch parallel convolution structure in combination with a self-adaptive weight adjustment mechanism based on feature response; training the licorice origin and cultivation type nondestructive identification model; and acquiring near infrared spectrum data of the to-be-classified liquorice, performing organization and standardization treatment, and performing nondestructive identification on the origin and the cultivation type of the to-be-classified liquorice subjected to standardization treatment by utilizing the trained liquorice origin and cultivation type nondestructive identification model. According to the method, multi-dimensional features can be fully mined, interference of redundant features and invalid information is not likely to happen, and therefore the liquorice classification precision is improved.

The invention provides a mobile terminal skin parameter inversion method based on spectral information, and the method comprises the following steps: constructing an optical model according to the characteristics of a skin layered structure and a spectral response mechanism of three skin parameters: melanin content, hemoglobin concentration and dermis thickness, and building a skin parameter and reflection spectrum database based on the model; based on the database, establishing a skin multi-parameter inversion MLP neural network structure adaptive to the collection characteristics of a mobile phone end sensor, and screening an optimal four-waveband channel through multi-waveband combination traversal; the mobile phone spectrum sensor is subjected to wave band optimization, data acquisition and skin parameter inversion. According to the method, through efficient decoupling of a nonlinear coupling relation among multiple skin parameters by waveband optimization and an MLP model, and targeted design of four optimal visible light narrow-band channels, synchronous quantitative detection of melanin, hemoglobin and dermis thickness is realized, core physiological parameters from epidermis to dermis superficial layer are covered, information coverage is comprehensive, and specificity is high.

The invention relates to the technical field of intelligent detection, in particular to a feed mycotoxin detection method and system based on spectral analysis. The method comprises the following steps: acquiring a near-infrared diffuse reflection spectrum of a feed sample to be detected, constructing an original spectrum vector based on absorbance data of the near-infrared diffuse reflection spectrum, and determining a projection component of the original spectrum vector on a pre-constructed qualified matrix space; subtracting the projection component from the original spectrum vector to obtain a residual vector, and calculating a first-order difference spectrum of the residual vector based on a preset sensitivity weight; and performing local feature weighting on the first-order difference spectrum to determine a weighted feature value, determining a residual entropy value of the residual vector and a range value of the residual vector, and determining a detection result of the to-be-detected feed sample by using the weighted feature value, the residual entropy value and the range value. According to the technical scheme, a more accurate detection result of the mycotoxin of the feed can be obtained.

The invention discloses a laser therapeutic instrument control method, equipment, a product and a medium, and relates to the technical field of medical instrument control. According to the method, an action area is divided into a plurality of operation units, and a reflection spectrum and a scattering spectrum of each operation unit are acquired in real time by utilizing a detection light beam, so that optical characteristic information of the tissue is accurately obtained; extracting multi-dimensional absorption characteristic parameters including a wave band absorption coefficient, a scattering attenuation coefficient and an effective penetration depth; a dose response function constructed based on the parameters can accurately represent a nonlinear mapping relation between the input laser energy and the actual absorbed dose; differential laser input parameters are reversely calculated through dose equalization processing, so that operation units with different optical characteristics can receive corresponding target absorbed doses; and finally, the laser therapeutic instrument executes operation according to the differentiated parameters, so that accurate energy control on areas with different optical characteristics is realized, and the effectiveness of laser treatment is improved.

The present application belongs to the technical field of grain informatization processing, and particularly relates to a kind of imperfect grain kernel identification method and system.Visible light image and reflectance spectrum data of grain kernel are input into identification model;From the features extracted from the visible light image and reflectance spectrum data of grain kernel respectively by the feature extraction module, the input features are obtained;The spectral Mamba branch in the identification model sequentially performs linear layer and convolution processing on the normalized input features, and then inputs the state space model to obtain the output;The spatial Mamba branch performs dimension transposition on the normalized input features, and then sequentially performs linear layer and convolution processing, and then inputs the state space model to obtain the output;The guide branch sequentially performs linear layer processing on the normalized input features, and then inputs the ConvNeXt classifier, and then adjusts the output of the ConvNeXt classifier combined with the SiLU activation function to obtain the output;According to the fusion result of the output of the guide branch, the spectral Mamba branch, the spatial Mamba branch and the input features, the identification result is obtained.

The present application relates to the technical field of display. Disclosed are a display substrate and a display apparatus. The display panel comprises a base substrate, a plurality of light-emitting units located in a display area of the base substrate, and a reflective metal layer located on at least part of the plurality of light-emitting units, wherein the reflective metal layer is used for adjusting a reflection spectrum of the display panel in a visible light band. Since the adjustment of a reflection spectrum can reflect a change in the reflectivity of the display panel, adjusting the reflection spectrum of the display panel by means of a reflective metal layer may mean that the reflective metal layer can be used for adjusting the reflectivity of the display panel. The change in the reflectivity has a certain impact on an always-on reflection hue of the display panel. Therefore, by means of providing the reflective metal layer, the flexibility of hue adjustment of the display panel can be improved.

This invention discloses a method and system for deep fusion detection of multimodal soil nutrients, belonging to the field of data processing. The method includes the following steps: real-time reception of multimodal data from a sensor suite deployed in the field. The received multimodal data includes soil reflectance spectral data collected by a near-infrared spectral sensor. Compared with the prior art, the advantages of this invention are: real-time reception of spectral, electrochemical, and image data, extraction of deep features after preprocessing and alignment, and introduction of a condition-aware network. The weights of each modality are dynamically adjusted based on auxiliary information such as soil moisture and organic matter content, and finally, a weighted fusion is performed to output the predicted nutrient value. This fully utilizes the complementarity of multimodal information, overcoming the environmental sensitivity and instability of single technologies while retaining their respective advantages, achieving rapid, accurate, and robust soil nutrient detection in the field.

The invention relates to the technical field of food safety detection and spectral analysis, in particular to a urine prohibited substance detection method based on double-line spectrum and contrastive analysis clustering, which comprises the following steps: respectively acquiring reflection spectrum signals of a T region and a C region of a detection card under different wavebands by using two spectrum sensors; respectively carrying out temperature compensation, denoising processing, smoothing processing and normalization processing on the reflection spectrum signals of the two regions; calculating a spectrum difference and a peak value ratio according to the reflection spectrum signals of the T region and the C region under different wavebands; judging whether the spectrum difference is smaller than a set threshold and the peak value ratio is smaller than the set threshold, and if not, outputting that the detected substance does not exceed the standard; otherwise, the detected substance exceeds the standard, and the concentration corresponding to the current spectrum difference is searched according to the concentration-spectrum difference mapping table. According to the invention, a detection result is automatically judged by a threshold difference analysis method, so that high-throughput, low-cost, rapid and objective field screening capability is realized.

The invention discloses a glass fiber pultrusion material density non-contact detection method, electronic equipment and a medium, and the glass fiber pultrusion material density non-contact detection method comprises the following steps: establishing a glass fiber pultrusion material density detection model based on a near infrared spectrum; and obtaining the original near-infrared diffuse reflection spectrum of the glass fiber pultrusion material to be detected and obtaining the density value of the glass fiber pultrusion material to be detected. By adopting the non-contact detection method for the density of the glass fiber pultrusion material, the electronic equipment and the medium, the non-destructive off-line detection of the glass fiber pultrusion material can be realized, the non-contact detection method is particularly suitable for the on-line detection of the glass fiber pultrusion material, and the non-contact detection of the density of the glass fiber pultrusion material can be realized by directly carrying out rapid and efficient non-destructive detection on a product at a production line outlet. A density detection result can be reflected to a production end in real time, so that real-time online optimization and adjustment of production process parameters are realized, and the production stability and the quality stability of the glass fiber pultrusion material are improved.

The invention discloses a system for improving the precision of film thickness measurement by a reflection spectrometry, which is characterized by comprising a white light source for emitting light in a wide spectral range; the main spectrograph is used for measuring the reflection spectrum of the measured object; the monitoring spectrometer is used for monitoring the spectral intensity of the light source in real time; the optical fiber assembly comprises a multi-core optical fiber and a single-core optical fiber and is used for conducting light from the light source to a measured object and conducting reflected light to the main spectrograph; and the data processing unit is used for calibrating the incident light intensity in real time according to the data of the main spectrograph and the monitoring spectrograph and calculating the thickness of the thin film. According to the system for improving the precision of measuring the thickness of the thin film through the reflection spectrum method, the repeatability precision of measurement and the stability of long-term measurement are improved.

An apparatus for intraoperative nerve identification and / or visualization of a target of interest of a living subject comprises a light source; an imaging head configured to acquire a polarized diffuse reflectance spectral image from the illuminated target of interest; and a controller configured to control the imaging head and to process the acquired polarized diffuse reflectance spectral image.

The present disclosure discloses a method and system for improving the accuracy of satellite remote sensing inversion by integrating hyperspectral proximal sensing, belonging to the technical field of water environment and aquatic ecological monitoring. The method includes the steps of: acquiring a water body hyperspectral proximal sensing reflectance spectrum dataset, a satellite remote sensing surface reflectance dataset, and a water environment in-situ measurement dataset, and performing preprocessing on the datasets; generating a fused satellite-ground dataset, and constructing and training a water quality parameter inversion model; and updating corresponding methods and the datasets in real time by repeating specified steps, thereby optimizing the model. The present disclosure displays and downloads inversion results according to a query instruction, enhances satellite spectral precision and increases the scale of the synchronous satellite-ground dataset, and is used for high-precision water environment monitoring.

The invention discloses a water area change whole process identification method and system based on a remote sensing image, and relates to the technical field of remote sensing monitoring, and the method comprises the steps: collecting a water area image through a multi-source remote sensing device, obtaining a water body reflection spectrum signal, and extracting water quality spectrum characteristic information and wave band parameters; identifying pollution polarization characteristic parameters in the water body reflection spectrum; based on the pollution gradient of the intersection of the main stream and the branch stream of the water area, pollutant scattering characteristic parameters are extracted; introducing wave band parameters as adjusting variables, determining wave band dependence terms, evaluating the pollution change degree of each monitoring section according to the corrected water body spectral refractive index, and generating a water area pollution change thermodynamic diagram. The technical problem that the water area pollution monitoring precision is insufficient due to the fact that an existing water quality monitoring method cannot effectively recognize the dynamic change of the complex water area is solved, and the technical effect of improving the water area pollution monitoring precision and efficiency through high-precision recognition and dynamic monitoring of the complex water area pollution characteristics is achieved.

The invention relates to the technical field of optical fiber sensing and optical fiber device manufacturing, and discloses a femtosecond laser-inscribing polarization-maintaining fiber grating method and system for vector sensing, and the method comprises the following steps: obtaining a stress region image of a polarization-maintaining fiber through a CCD camera, recognizing the slow axis direction of the fiber through image processing, rotating the fiber, and obtaining the stress region image of the polarization-maintaining fiber; an included angle of 45 degrees is formed between the slow axis direction and a preset incident plane of the femtosecond laser; calculating a conjugate phase of wavefront aberration generated when femtosecond laser penetrates through a fiber coating layer and a cladding and is focused to a fiber core, and generating a phase diagram for loading a spatial light modulator; after being modulated by the spatial light modulator, a light beam emitted by the femtosecond laser enters and is focused on the fiber core along the direction of an included angle of 45 degrees, and a grating structure is formed by combining axial scanning and inscribing. Accurate automatic alignment in the fast and slow axis direction and active compensation of transmission aberration are achieved, refractive index modulation birefringence forming a specific included angle with the inherent birefringence axis of the optical fiber can be effectively induced, and therefore the polarization-maintaining fiber grating with the highly controllable reflection spectrum and the asymmetric double-peak characteristic is engraved.

The invention discloses a fiber bragg grating production control system and method, and belongs to the technical field of optical fiber sensor manufacturing, and the method comprises the steps: obtaining a pre-stress spectrum curve and an ultraviolet laser parameter set of a target optical fiber before writing, and constructing a feature vector reflecting the disturbance sensitivity of the optical fiber; in the laser writing process, acoustic emission signals and laser parameters are collected in real time, and a joint disturbance function is constructed; identifying a nonlinear stress disturbance event through dynamic matching with the sensitive feature vector, and extracting occurrence time and disturbance intensity of the nonlinear stress disturbance event; constructing a prediction model based on disturbance history, predicting a future disturbance trend and adjusting laser parameters; after writing, a grating reflection spectrum is collected and compared with a target template spectrum, and if the similarity requirement is not met, a disturbance error path is traced back, and parameter compensation writing is executed; according to the invention, real-time perception and response regulation and control of micro-disturbance can be realized, and the writing precision and consistency of the fiber bragg grating are improved.

The invention comprises a method and system for cost effective, convenient remote high fidelity color reproduction and matching that can be used to convey color to observers remote from the physical source of color. Such remote observers can include product consumers wishing to view a product color, for example. In a preferred embodiment, the method comprises capture of article or product reflectance spectra and the use of this spectrum to filter ambient light or directed light in the environment of a user remote from the article or product. Other embodiments of methods include various techniques to capture product spectral information and color matching functions useful for color reproduction using colored light sources. Additional systems embodiments include devices exploiting multiprimary displays to render the product color with reduced metamerism.

The invention discloses a marine mixed layer water environment parameter measurement method and system based on a stimulated Brillouin scattering acoustic grating, and relates to the field of marine water environment detection.The method comprises the steps that a dependency equation between stimulated Brillouin scattering frequency shift and water environment parameters is established, and a first dependency equation is obtained; the water body environment parameters comprise temperature and salinity; establishing a dependency relationship equation between the acoustic grating reflection spectrum center peak value frequency shift and the water body environment parameters to obtain a second dependency relationship equation; and calculating water body environment parameters based on the first dependency relationship and the second dependency relationship. According to the invention, complete distinguishing of marine mixed layer water body environment parameters can be realized, and the measurement precision is high.

The utility model belongs to ceramic detection equipment technical field especially relates to a kind of ceramic whiteness real-time detection device in high-temperature calcination process, including base assembly, base assembly is connected with support adjusting assembly through support, cooling and temperature reducing component is connected on the upper end of support adjusting assembly, high-spectrum camera is clamped in cooling and temperature reducing component middle, base assembly is connected with the water inlet end of shell-and-tube water cooler through water pump, cooling and temperature reducing component is connected with the water outlet end of shell-and-tube water cooler, high-spectrum camera is erected at the observation window outside of high-temperature calcination chamber, high-spectrum camera captures the reflection spectrum information of kiln ceramic surface, this spectrum data is uploaded to processor, and the whiteness value that meets CIE whiteness standard or specific industry standard is calculated, and the whiteness change of ceramic can be monitored in real time and continuously by high-spectrum camera, and powerful technical support is provided for quality control in ceramic production process.

The invention relates to a vegetation leaf dry matter content remote sensing high-precision inversion method based on wavelet analysis. The method comprises the following steps that S1, a leaf sample database is constructed; S11, a leaf actual measurement data set is constructed; s12, constructing a blade simulation data set; s13, data set division: dividing an actual measurement data set into an actual measurement training set and an actual measurement verification set according to wavelet features; s2, extracting dry matter feature information through wavelet transform; S2, performing multi-scale decomposition on the leaf spectral signal by using continuous wavelet transform; s22, adopting Morlet wavelet as a generating function to carry out continuous wavelet transform analysis on the original reflection spectrum of the blade; s23, carrying out correlation test on the obtained wavelet coefficient and an LMA value; s24, according to a set threshold value, wavelet coefficient characteristics sensitive to the dry matter content are screened out; and S3, constructing an LMA inversion model based on the wavelet coefficient characteristics and the spectral indexes. The method is high in inversion precision, strong in robustness and good in stability.

The invention provides a multi-component thin film evaporation film thickness monitoring and adjusting device and method and application, the multi-component thin film evaporation film thickness monitoring and adjusting device comprises a conveying module used for conveying a substrate so as to deposit a film layer on the moving substrate through a first evaporation source and a second evaporation source, the conveying module is provided with a position sensing module, and the position sensing module is used for sensing the position of the film layer on the moving substrate through the first evaporation source and the second evaporation source; a trigger signal is generated when the substrate enters the set area; the first film thickness monitoring module is used for acquiring the deposition speed of the first evaporation source and the thickness of a film layer deposited on the substrate; the second film thickness monitoring module is used for acquiring a reflection spectrum of the second evaporation source in a set area; and the control module is used for obtaining the film thickness according to the reflection spectrum of the second evaporation source through an inversion algorithm, and independently feeding back and controlling the real-time evaporation working condition. The thickness of materials with different evaporation rates is subjected to differential parallel monitoring, a closed-loop feedback system is formed, the film thickness monitoring accuracy is improved, and long-time operation of monitoring work is guaranteed.