3444results about "Transmissivity measurements" patented technology

The invention discloses an online monitoring method and system for the light transmittance of an optical lens, and relates to the technical field of precise optical detection. The objective of the invention is to solve the problem of large light transmittance calculation error caused by halo scattering noise interference, low optical path calibration precision of a complex curved lens, a measurement blind area of a large-aperture lens and environmental disturbance of a high-reflection / high-light-transmittance lens in the prior art. According to the scheme, a three-dimensional curved surface model is constructed based on Gray code structured light projection and ICP registration, a dynamic partition scanning instruction set is generated through an improved genetic algorithm, and multi-wavelength polarized light is driven to scan and collect multi-dimensional data; specular reflection and scattering noise are suppressed by combining an improved Stokes vector algorithm and an attention mechanism U-Net network, and the data precision of the complex curved surface is improved by adopting Bayesian optimization and Zernike polynomial weighted fusion; constructing a double-loop coupling optimization architecture to realize closed-loop adaptive optimization; according to the invention, the anti-interference capability, the complex lens adaptability and the full-aperture detection precision are obviously improved.

The invention belongs to the technical field of water quality monitoring, and particularly relates to a construction method and device of a turbidity testing system based on a photoelectric detector. Optical signal data and multi-wavelength optical signal data are obtained; performing intelligent switching and spectrum matching according to the signal data, determining a target wavelength, and obtaining characteristic parameters related to turbidity by combining a scattering and transmission combined measurement principle; measuring different standard solutions according to the characteristic parameters to obtain corresponding characteristic parameters, constructing a turbidity characteristic parameter data set, and establishing a characteristic ratio turbidity calibration model according to the data set; measuring and calculating the turbidity according to the characteristic ratio turbidity calibration model in combination with a dynamic temperature compensation algorithm, and meanwhile, performing temperature compensation; and transmitting the parameter information to a cloud database for storage, performing hierarchical processing, performing regular intelligent self-inspection at the same time, and feeding back abnormal data when an abnormality occurs. Therefore, the problems of insufficient range coverage, weak automatic calibration capability, susceptibility to temperature drift and the like in the prior art are solved.

The invention discloses a solar silicon wafer visual detection method, and particularly relates to the technical field of silicon wafer detection. The method comprises the following steps: acquiring optical images of different incident angles, synchronously acquiring infrared transmission images, performing normalization processing, edge enhancement filtering and self-adaptive threshold segmentation on the acquired multi-angle images, extracting suspected crack areas, and respectively calculating a gray gradient change rate and a stress abnormal degree, so as to obtain a suspected crack area; calculating a crack credibility score according to the gray gradient change rate and the stress abnormal degree through a weighted scoring method, and comparing the crack credibility score with a preset crack detection threshold value to distinguish real hidden cracks and stress pseudo defects; if the credibility score is lower than the threshold value, secondary sampling is carried out by adjusting the illumination angle, and the judgment result is further optimized; according to the method, the false rejection rate caused by lattice stress pseudo defect misjudgment is effectively reduced, meanwhile, missing detection of real subfissures is avoided, and the accuracy, stability and production yield of silicon wafer defect detection are improved, so that the long-term reliability of a photovoltaic module is enhanced.

The invention relates to the technical field of glass detection, and discloses a method, a device and equipment for detecting glass after light sweeping. The method comprises the following steps: collecting multi-source original sensing data of glass to be detected, carrying out signal denoising, synchronous transformation and multi-scale glass feature extraction on the multi-source original sensing data, and carrying out feature combination, feature dimension reduction compression, region segmentation and region contour reconstruction on the multi-scale glass features to obtain an initial defect region set; performing spatial-temporal feature combination of multi-source features on the initial defect region set to obtain an enhanced defect feature set; and constructing a region similarity matrix corresponding to the enhanced defect feature set, performing defect category judgment and multi-dimensional glass quality scoring on the region similarity matrix to obtain glass quality evaluation data, performing process association on the glass quality evaluation data, and generating a final detection report of the to-be-detected glass. According to the method, the result accuracy of quality detection on the glass subjected to light sweeping is improved.

The invention relates to the technical field of intelligent detection, and discloses a water pollutant concentration intelligent detection system and a detection method thereof, and the water pollutant concentration intelligent detection method comprises the following steps: obtaining optical data, chemical data, electrical data, environmental data and biological data; performing normalization and standardization processing on the obtained data through edge calculation; performing feature extraction on the acquired data; splicing the features to obtain a fused feature; the fusion features are input into a multi-layer perceptron for water pollutant concentration prediction; the diffusion conditions of pollutants at different time points in the future are predicted through a fluid mechanics formula; inputting the fusion features into a decision tree model, and judging the instant influence of the water pollutants on the cultured organisms; the breeding environment parameters are adjusted through instant influence. According to the method, through edge calculation, behaviors of aquatic organisms are combined, and the diffusion trend of water pollutants is predicted, so that more accurate water quality monitoring is realized.

The invention discloses a multi-mode end point detection system and method for a semiconductor dry process, and relates to the field of gas concentration detection. A gas absorption cell; the reference light path adjusting unit comprises an adjustable attenuator used for adjusting signals; the first photoelectric detector is used for detecting a transmission signal; the second photoelectric detector is used for detecting a reference signal; the lateral scattered light detector is used for detecting a scattered signal of the particulate matters in the gas absorption tank; and the signal processing unit is in signal connection with the first photoelectric detector, the second photoelectric detector and the lateral scattering light detector and is used for performing compensation calculation on the transmission signal based on the reference signal and the scattering signal so as to obtain a corrected gas absorption signal. By adopting the scheme, measurement signal distortion caused by optical mirror surface pollution and particulate matter scattering interference in a semiconductor tail gas optical detection technology is avoided.

The invention belongs to the technical field of detection, and discloses a gas concentration infrared sensor and a detection method thereof.The detection method comprises the steps that transmittance data of two channels of the infrared sensor are collected in real time, and meanwhile sensor surface temperature and environment humidity parameters are obtained to form a multi-parameter synchronous collection data set; establishing a humidity compensation function based on the collected environment humidity parameters, dynamically correcting the transmittance of the main detection channel, judging the condensation risk according to the transmittance change rate of the reference channel, calculating the transmittance change rate of the main detection channel, extracting the humidity interference characteristic quantity of the reference channel, and generating fusion characteristic parameters; performing gas existence judgment, and triggering a gas existence flag bit; according to a gas existence flag bit state, adopting a temperature self-adaptive response value calculation method and combining environment compensation parameters to carry out concentration conversion, and outputting a gas concentration value; and through a multi-parameter synchronous acquisition and environment compensation mechanism, the problem of environment interference in a high-temperature and high-humidity environment is effectively solved, and the measurement accuracy is improved.

The invention discloses a pork quality grade lossless evaluation method based on hyperspectral imaging, and relates to the technical field of pork detection.The pork quality grade lossless evaluation method comprises the following steps that pork samples of different qualities are prepared, and standardization processing is conducted on the pork samples; performing chromatic aberration analysis on the pork samples with different qualities by using a colorimeter, and performing quality grade division on the pork samples with different qualities based on the analysis results of the muscle color, the fat color and the gloss of the pork. According to the pork quality grade lossless evaluation method based on hyperspectral imaging, reflection or transmission information of a pork sample in a plurality of continuous spectral wavebands is captured by using a hyperspectral imaging technology, accurate evaluation of the pork quality grade is realized by analyzing spectral data, higher-dimension data is provided, and the evaluation accuracy of the pork quality grade is improved. Meanwhile, rapid scanning can be achieved, the detection time is greatly shortened, the overall detection efficiency is improved, and pork quality monitoring is more efficient and timely.

The present invention belongs to the technical field of LiDARs, and particularly relates to a system and method for synchronous detection of atmospheric data in the same path. The detection system comprises a transmitting unit, a receiving unit and a data processing unit, wherein the transmitting unit comprises a plurality of laser devices, and is used for synchronously transmitting laser having different wavelengths in a common path; the receiving unit comprises a receiving telescope, which is symmetrically provided with a plurality of sub-apertures used for receiving echo signals that are generated after the laser having different wavelengths interacts with the atmosphere; and the data processing unit is used for calculating atmospheric data parameters by means of the echo signals. By means of the present invention, synchronous detection of a plurality of atmospheric data parameters in the same path can be implemented.

The invention relates to the technical field of optical detection, in particular to a glass bottle surface spraying quality detection method which comprises the following steps: under a specified wavelength, acquiring target incident light by adjusting a polarization angle, irradiating a glass bottle spraying layer, collecting a transmission spectrum signal to calculate parallel and vertical polarization transmissivity and ratio of the spraying layer, and generating polarization transmissivity. According to the method, the light with the polarization angle irradiates the spraying layer, the polarization component of the transmission light is obtained, the thickness uniformity and the internal structure are analyzed, weak areas, particle flaws and excessive spraying of the spraying layer are recognized, the defect detection precision is improved, multi-angle transmissivity data are collected, the change rate is calculated, and color deviation and thickness abnormity are accurately positioned; through cross analysis of multiple optical parameters, evaluation of adhesive force, curing quality and color consistency is more detailed, spraying abnormity is classified, multiple detection means act synergistically, interference such as environment illumination and material reflectivity is reduced, and the detection accuracy of spraying quality is improved.

The invention relates to the technical field of spectrum analysis, in particular to an intelligent protein quality detection method and system based on spectrum analysis, and the method comprises the following steps: collecting infrared spectrum data of a preset number of protein samples; determining a local fluctuation coefficient of the transmittance of each wavelength; determining a fluctuation coefficient of the infrared spectrum data of each protein sample; screening the infrared spectrum data of all the protein samples based on the fluctuation coefficient to obtain fluctuation data of each suspected impurity; equally dividing each piece of suspected impurity fluctuation data into each fragment; determining an abnormal index of the suspected impurity fluctuation data in each segment; correcting a spatial domain weight and a value domain weight of each filtering window in a bilateral filtering algorithm based on the abnormal index, and denoising infrared spectrum data of the protein sample; and determining a difference coefficient of the infrared spectrum data of each protein sample, and detecting the protein quality. Therefore, the accuracy of protein quality detection is improved.

The invention discloses a waveguide array gas sensing system for high-sensitivity multi-gas detection. The waveguide array gas sensing system comprises a waveguide substrate, and a waveguide Bragg grating, a phase shift Bragg grating, a micro-ring resonator, a Mach-Zehnder interferometer, a waveguide array, an electric field regulation and control module and a signal processing unit which are arranged on the waveguide substrate. Through the waveguide array structure, topological optical protection adsorption and other technologies, the sensitivity and selectivity of methane, carbon dioxide and other gases are effectively improved, and accurate detection can be achieved in a complex environment; according to the invention, a topological optical principle is adopted, signal loss caused by environmental noise or surface defects is reduced, and the stability of the sensor is improved; according to the invention, automatic calibration and temperature and humidity compensation of the system are realized, and autonomy and operation convenience of the system are enhanced; the system has high environment adaptability and can stably work under different temperature and humidity conditions.

The invention discloses an NO and SO2 mixed gas concentration detection method based on deep learning, and the method comprises the steps: obtaining a to-be-detected NO and SO2 mixed gas, inputting the to-be-detected NO and SO2 mixed gas into a trained mixed gas concentration detection model, and obtaining the concentration detection results of the respective single gases of NO and SO2; according to the model, mixed gas spectrum separation and reconstruction are carried out through a separation and reconstruction model based on a bidirectional long-short-term memory network, so that differential absorption spectrums of two single gases NO and SO2, which are output by the separation and reconstruction model, are obtained at one time; and carrying out feature extraction and concentration prediction on the input sequence data through a concentration detection model based on TCN + RNN network so as to obtain concentration detection results of respective single gases of NO and SO2 as outputs. The method provided by the invention can realize spectral separation of the mixed gas and accurate detection of the concentration of NO and SO2, thereby overcoming the problems of cross sensitivity of SO2 and NO and differential optics of incapability of accurately separating SO2 and NO by a traditional treatment method.

Prediction of water quality parameters via monitoring, reporting, and verification sensor-geospatial fusion networks may be provided by a system comprising a plurality of separate water fixtures, wherein each of the plurality of separate water fixtures includes: an optical sensor, and a data transmission system configured to transmit sensor data from each of the plurality of separate water fixtures; and a contamination detection system configured to: receive sensor data from each of the plurality of separate water fixtures and remote sensing data; calculate changepoints within the sensor data; split the data into intervals at the changepoints; classify the intervals using a machine learning model; and identify a predicted contamination of a water source based on the classified intervals using the sensor data from a subset of the plurality of separate water fixtures and the remote sensing data to yield a near-time estimation of water quality parameters.

The invention discloses a liquid medicine foreign matter detection method and system based on machine vision, and the method comprises the steps: obtaining multiband spectral data of a liquid medicine sample, and carrying out the normalization processing to generate a liquid medicine background standard spectral feature template; comparing the refractive index spectral characteristics of the template and the foreign matter-containing liquid medicine, and recording the surface roughness scattering mode and polarized light reflection angle change data of a foreign matter area; calculating a spectrum peak displacement quantized value according to the polarized light data, and extracting foreign matter edge spectrum gradient information in combination with a threshold value; calculating a transparency spectral attenuation coefficient based on the edge gradient information, and obtaining spectral contrast enhancement factors of different foreign matters in combination with the spectral response characteristic data; and if the enhancement factor does not reach the standard, adjusting the spectrum correction parameter and recalculating, fusing the scattering mode and the multi-angle incident spectrum response result to carry out consistency verification, and obtaining a final identification result containing the foreign matter material type and the danger level. The method can improve the drug detection accuracy and guarantee the drug quality safety.

The invention provides a pole piece detection method, a detection device, detection equipment and a storage medium. The pole piece detection method comprises the following steps: acquiring first detection data corresponding to a composite coating on a pole piece irradiated by a first light beam and second detection data corresponding to the composite coating irradiated by a second light beam; based on the first detection data and the second detection data, determining the proportion of a target component in the composite coating; determining the surface density of the composite coating based on the second detection data; determining the surface density of the target component based on the proportion of the target component and the surface density of the composite coating; the correlation coefficient between the absorption coefficient of the first light beam and the atomic number is larger than the correlation coefficient between the absorption coefficient of the second light beam and the atomic number. Based on the mode, the surface density of the target component in the composite coating can be determined.

The invention discloses a detection method and system for a flue gas analyzer, and the method comprises the steps: carrying out the spectrum scanning of flue gas through a multispectral detector according to the spectral characteristics of the flue gas, and obtaining the reflection and transmission spectrum data of the flue gas in a plurality of wavelength ranges; establishing an abnormal value detection model by using an ensemble learning algorithm according to the spectral data so as to process the spectral data; analyzing the processed spectral data in real time, and identifying smoke components and concentration data thereof; a dynamic adaptability correction model is constructed according to real environment conditions, historical flue gas components and concentration data of the historical flue gas components so as to correct the concentration data of the identified flue gas components in real time, and the working state of the multispectral detector is adjusted through a feedback control unit; and monitoring data of a related environment where the flue gas is located, and integrating the corrected flue gas component and concentration data and the related environment data by using a data fusion algorithm to generate a flue gas analysis report. By utilizing the embodiment of the invention, the flue gas components can be monitored in real time, the defects of a traditional analysis instrument in the aspects of data processing and correction are overcome, and the accuracy and reliability of flue gas analysis are improved.

The invention relates to a USB interface quality detection method, system and terminal, and relates to the field of automobile parts, and the method comprises the steps: determining model information from a preset model database according to housing detection information; determining an illumination position, an illumination brightness value and reference transmittance according to the model information; according to the illumination position, a preset illumination device is controlled to be lightened with the illumination brightness value to obtain illumination detection information; obtaining illumination transmittance according to the illumination detection information; if the illumination light transmittance is consistent with the reference light transmittance, light transmittance detection is completed; if the light transmittance is not consistent with the reference light transmittance, an abnormal position is marked; according to the shell detection information corresponding to the abnormal position, material shortage shape information is determined, and a corresponding material supplementing block is manufactured; and repairing the material supplementing block to the corresponding outer cover or base according to the abnormal position and the material supplementing block. According to the invention, the USB interface is automatically detected, the efficiency is improved, and errors are reduced.

Modulation-encoded light, using different spectral bin coded light components, can illuminate a stationary or moving (relative) target object or scene. Response signal processing can use information about the respective different time-varying modulation functions, to decode to recover information about a respective response parameter affected by the target object or scene. Electrical or optical modulation encoding can be used. LED-based spectroscopic analysis of a composition of a target (e.g., SpO2, glucose, etc.) can be performed; such can optionally include decoding of encoded optical modulation functions. Baffles or apertures or optics can be used, such as to constrain light provided by particular LEDs. Coded light illumination can be used with a focal plane array light imager receiving response light for inspecting a moving semiconductor or other target. Encoding can use orthogonal functions, such as an RGB illumination sequence, or a sequence of combinations of spectrally contiguous or non-contiguous colors.

The invention discloses a three-dimensional turbidity measurement method and system based on space scanning, and the method comprises the steps: building a three-dimensional xyz coordinate system in a to-be-measured three-dimensional space, respectively scanning and measuring an xoz coordinate plane and a yoz coordinate plane, and obtaining meshed turbidity data; and calculating the turbidity CNTU of the three-dimensional space based on the planar or single-dimensional turbidity data of the xoz coordinate plane and the yoz coordinate plane. According to the method, turbidity data of the xoz coordinate plane and the yoz coordinate plane can be processed through a plane calculation method, and the turbidity of the three-dimensional space reflecting the overall measurement condition can be obtained through quick calculation. On the other hand, the turbidity data of the xoz coordinate plane and the yoz coordinate plane can be processed through a one-dimensional calculation method, the turbidity of the three-dimensional space can be calculated more accurately, the requirement for high precision of turbidity measurement of the three-dimensional space is met, the limitation of single-point measurement is solved, and good practicability is achieved.

The invention discloses a PVC film performance detection method and system based on a machine vision technology, and relates to the field of PVC film detection. According to the technical scheme, the method comprises the following steps: performing visual inspection on a to-be-detected PVC film sample to obtain defect characteristic parameters of the to-be-detected sample, performing performance test on the to-be-detected PVC film sample to obtain performance index parameters of the to-be-detected sample, and performing gray correlation analysis on the performance evaluation parameters and the defect characteristic parameters to obtain the to-be-detected PVC film sample. The method comprises the following steps: acquiring a performance index of a PVC film and a defect characteristic parameter, acquiring a correlation degree between the performance index of the PVC film and the defect characteristic parameter, constructing an evaluation model according to the acquired parameter and the correlation degree, and calculating a performance evaluation quantized value of the to-be-detected PVC film through the model. According to the invention, real-time performance detection can be carried out on the PVC film in the production and processing process, and a traditional detection mode of sampling a formed finished film is not needed, so that the production and performance detection efficiency of the PVC film is improved, and the detection complexity is reduced.

The invention discloses a seawater quality AI fusion intelligent monitoring system and method based on full spectrum data, and relates to the technical field of seawater quality monitoring. The system comprises a full-spectrum data acquisition module, a water quality initial evaluation and characteristic wave band identification module, an environment adaptive wave band selection module, a weight dynamic distribution and anomaly detection module, a multi-dimensional data fusion and optimization module and an abnormal event response and report module. The system collects original spectral data through a spectral sensor, establishes a basic water quality model after preprocessing, dynamically selects an effective wave band according to real-time environmental parameters, allocates weights, outputs water quality parameters after fusing data of a multi-dimensional sensor, and finally responds to abnormal events and generates a report. The system realizes intelligent and real-time monitoring of seawater quality, and can effectively deal with sudden pollution events and capture water quality fluctuation.

The invention relates to a three-dimensional aquatic vegetation canopy reflection characteristic modeling method based on a real scene. The method comprises the following steps that leaf reflection and transmission spectrums are obtained through calculation of a plant leaf radiation transmission model; in combination with an actual aquatic vegetation scene, vegetation canopy reflection characteristics are described through canopy structure parameters and leaf BRDF; calibrating model parameters by adopting four-flow approximation and linear approximation, and applying the model parameters to approximate solution of vegetation canopy reflectivity; finally, a LuxCoreRender physical rendering engine is used for coupling input parameters such as incident radiation, vegetation canopy reflection factors, water optical attribute parameters and observation geometry, and the vegetation canopy reflectivity is calculated in combination with an aquatic vegetation scene. According to the method, a high-precision three-dimensional aquatic vegetation canopy reflection model is established, remote sensing radiation modeling precision and application value can be improved, an important tool platform is provided for wetland remote sensing monitoring and ecological protection and coastal wetland blue carbon sink function evaluation, and the method has popularization and application prospects.

The invention relates to the technical field of peritoneal drainage, in particular to a peritoneal drainage system based on hemoglobin real-time monitoring and intelligent early warning. According to the technical scheme, the device comprises an abdominal cavity drainage tube, an optical sensing module, a microprocessor module and a wireless communication module, wherein the microprocessor module is configured to perform moving average filtering and dynamic trend modeling on hemoglobin concentration data; and triggering early warning according to a preset multi-level alarm condition. The hemoglobin concentration in the peritoneal drainage liquid is accurately monitored in real time, intelligent early warning and a personalized response mechanism are combined, the limitation of traditional manual observation is broken through, the timeliness and accuracy of bleeding risk identification are remarkably improved, the infection risk is reduced through the closed design, the medical care working process is optimized through the system integration capacity, and the medical care efficiency is improved. Data sharing and remote cooperation are achieved, intervention time windows are shortened, patient prognosis is improved, nursing resources can be released, medical quality is improved, and a comprehensive and efficient solution is provided for postoperative monitoring.

The invention belongs to the field of water body pollution monitoring, and discloses a water body micro-plastic monitoring method and system based on unmanned aerial vehicle optics and Raman spectrum technology, a multi-mode water body micro-plastic sensor based on optical imaging and a hyperspectral Raman laser radar is constructed, and the constructed sensor is used for collecting water body micro-plastic data; establishing a solar flare correction model and an underwater light attenuation compensation model to pre-process the collected water body micro-plastic data; performing water body micro-plastic detection on the preprocessed data by using a multi-mode underwater micro-plastic semantic segmentation model; a spatial and temporal distribution model of micro-plastic pollution in the urban water body is constructed, and migration and accumulation, main sources, future distribution trend and the like of micro-plastics in the water body are comprehensively analyzed. According to the invention, the problems of incapability of large-scale real-time detection, large interference of a water body environment and the like in a traditional water body micro-plastic detection method can be effectively solved, and the capability and efficiency of water body micro-plastic detection by using the unmanned aerial vehicle are greatly improved; reliable data support and technical guarantee are provided for water body pollution monitoring, ecological environment assessment and micro-plastic treatment, and large-scale water body monitoring and environment protection work are promoted to be carried out.

The invention belongs to the technical field of terahertz detection, and discloses a terahertz metamaterial enhanced spectrum detection system. Comprising the following steps: constructing a metamaterial enhancement factor tensor matrix according to the interaction between terahertz waves and a metamaterial; performing local field enhancement and surface plasma resonance optimization on the target sample based on the metamaterial enhancement factor tensor matrix to obtain a feature enhancement spectroscopy mapping function; constructing a multi-dimensional detection feature space based on a feature enhancement spectroscopy mapping function; a spectral signal enhancement topology network is formed based on the multi-dimensional detection feature space; enhancing the topological network based on the spectral signal, and generating an enhanced spectral feature discrimination function; obtaining a high-precision terahertz spectrum detection result based on the enhanced spectrum characteristic discrimination function; according to the invention, internal correlation between spectral characteristics can be mined, and comprehensive description of sample information is enhanced, so that high-precision terahertz spectrum detection is realized.

The invention relates to the technical field of light transmittance detection devices, in particular to a light transmittance detection device for agricultural film production. Comprising a detection host; the detection probe is fixedly connected to the upper side of the detection main machine through a stand column, guide rails are installed on the two sides of the detection main machine, the guide rails are connected with electric sliding blocks in a sliding mode, and the electric sliding blocks are rotationally connected with carrier rollers; the electric push rod is fixedly connected to a stand column of the detection host, the extrusion assembly is provided with a fixed sliding rail, sliding grooves are formed in the two sides of the fixed sliding rail, and the fixed sliding rail is located above the guide rail; and the number of the sliding pieces is two, the two sliding pieces are connected into the sliding grooves of the fixed sliding rails in a sliding mode correspondingly, and the sliding pieces are rotationally connected with extrusion rollers. The two groups of carrier rollers and extrusion rollers are used for mutually extruding to flatten a film towards the left side and the right side, so that the bending degree of the film is reduced, and the influence of folds of the film on the light transmittance of the film is weakened.

The invention discloses a light transmission detection device and method for an optical polished section, and relates to the technical field of optical detection.The light transmission detection device comprises a detection chamber and a mechanical arm, the mechanical arm is arranged outside the detection chamber, a detection mechanism is arranged at the upper end of the interior of the detection chamber, and a light source is further arranged in the detection chamber; the detection mechanism is composed of a rotating assembly and a clamping assembly, a suction cup clamp is arranged at the execution end of the mechanical arm and composed of a fixed cover and a movable column, the movable column is installed in the fixed cover, a spring is arranged between the movable column and the fixed cover, and a lens suction cup is arranged at the end, away from the mechanical arm, of the movable column. Negative pressure for adsorbing the optical polishing piece is generated through a mechanical structure, the cost of the air pump is saved, falling of the optical polishing piece caused by sudden shutdown of the air pump is also avoided, and the reliability of the system is improved.

The invention provides a spatial continuous visibility prediction method and device based on multi-modal data analysis, and the method comprises the steps: obtaining the multi-modal observation data of a target region, carrying out the image feature coding of the image observation data, generating an atmospheric optical thickness parameter, carrying out the path feature coding of the laser radar scanning data, and carrying out the path feature coding of the laser radar scanning data; generating an extinction coefficient distribution parameter; inputting the atmospheric optical thickness parameter and the extinction coefficient distribution parameter into a multi-modal fusion model to perform optical thickness correction on the atmospheric optical thickness parameter in the horizontal direction to generate a horizontal optical thickness correction parameter, and performing spatial continuous fusion on the horizontal optical thickness correction parameter and the extinction coefficient distribution parameter to obtain a multi-modal fusion model; and generating a spatial continuous visibility distribution characteristic of the target area, then converting the spatial continuous visibility distribution characteristic into a visibility prediction result under a polar coordinate system, and outputting a coordinate distribution diagram of the visibility prediction result. According to the invention, the visibility prediction accuracy can be improved.

Methods and apparatus for processing a substrate are provided herein. For example, a gas supply configured for use with a processing chamber includes an ampoule that stores a precursor and comprises an input to receive a carrier gas and an output to provide a mixture of the carrier gas and the precursor to the processing chamber and a sensor assembly comprising a detector and an infrared source operably connected to an outside of an enclosure, through which the mixture flows, and a gas measurement volume disposed within the enclosure and along an inner wall thereof so that a concentration of the precursor in the mixture can be measured by the detector and transmitted to a controller.