3430 results about "Scattered light" patented technology

The invention discloses a PCB three-proofing coating quality detection method and system. The method comprises the steps that a visible light reflection image of the surface of a PCB and scattering spectrum data of a near-infrared band are acquired; performing spatial filtering processing on the visible light reflection image to extract interface area pixels, calculating coating layer thickness gradient distribution based on Mie scattering characteristics in scattering spectrum data, and fusing to generate an edge gradient distribution map; and according to the gradient amplitude change rate in the edge gradient distribution map, segmenting the effective coverage area of the coating layer by adopting a self-adaptive dynamic threshold algorithm, and extracting curvature extreme point density and boundary fractal dimension parameters at the segmentation boundary. According to the invention, three technical barriers of difficult microdefect capture, unmeasurable interface performance and delayed failure risk in traditional detection are solved, and two-dimensional accurate diagnosis of the structural compactness and interface reliability of the coating layer is realized.

The invention discloses a water quality heavy metal pollution detection method and system based on Raman spectrum.The water quality heavy metal pollution detection method comprises the steps that water body Raman scattering light is collected in situ through a miniature optical fiber probe, and a continuous time sequence spectrum signal flow is generated; wavelet transform is combined with self-adaptive threshold setting, and high-frequency noise and effective spectral signals are separated; dynamically strengthening the characteristic peak of the target heavy metal through a frequency domain characteristic screening module, and inhibiting a water molecule interference peak at the same time; generating a cross-domain fusion feature vector; processing the fusion feature vector through a pre-trained heavy metal concentration prediction model, and outputting concentration prediction values of various heavy metals; a confidence score is dynamically calculated based on a deviation between a current predicted value and historical data distribution, and model parameter update and system calibration are automatically triggered. The method has the advantages that through acousto-optic signal cross-domain fusion and closed-loop self-calibration, the target peak is dynamically strengthened while water molecule interference is inhibited, and the real-time performance, the anti-interference performance and the prediction precision of heavy metal detection are improved.

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention belongs to the technical field of automatic detection, and discloses an online laser detection and grading regulation and control system for particle size distribution of crushed raw ore. The invention aims to solve the problems of halo effect interference caused by adhesion of fine dust in a complex industrial environment and insufficient detection precision of a traditional method. The system obtains dynamic scattering light field data through the laser scanning module, identifies a halo effect region and generates a compensation coefficient by using the light field preprocessing module, and realizes accurate reconstruction of particle boundaries in combination with the edge reconstruction module. The particle size distribution analysis module extracts multi-dimensional geometric features based on the accurate boundary data, and generates a real-time particle size distribution curve. The grading strategy generation module formulates a regulation and control strategy according to deviation characteristics of the curve and a preset standard, and the dynamic regulation and control module adjusts parameters of crushing equipment in real time and optimizes particle size distribution. The method effectively overcomes the halo effect interference, improves the detection precision and the system stability, breaks through the single limitation of a traditional method, and provides comprehensive data support for a downstream process.

The invention relates to the technical field of optical lens defect detection, and particularly discloses an optical lens laser-induced damage on-line detection method and system, a linear polarizer and a narrow-band filter are connected in series in a detection laser light path, non-target polarized light is filtered through polarization direction matching, meanwhile, interference of the environment and scattered light is inhibited through the narrow-band filter, and the laser-induced damage on-line detection system is obtained. According to the method, external source noise such as ambient light and non-target polarized light is reduced through polarization matching and narrow-band filtering, randomness of speckle noise is offset through multi-angle collection and signal fusion in a visual detection mode, exposure is dynamically adjusted, an image is fused to improve the signal-to-noise ratio, noise and real signals are decoupled through self-supervised learning, and the real-time performance of the system is improved. Dust interference is removed in combination with morphological operation; a deep learning reasoning model enhances the damage identification capability in a noise environment, defocusing blur caused by mechanical vibration is eliminated through phase conjugate correction, and the influence of photoelectric conversion noise, dust interference and the like on the detection efficiency and accuracy is remarkably reduced through multi-link linkage.

The invention relates to the technical field of precision detection, in particular to a device and a method for nondestructive testing of a wafer surface. The device provided by the invention comprises a detection light path, a motion control module, a narrow channel detection end, a wide channel detection end and a data acquisition and processing module, the motion control module is used for bearing a to-be-tested wafer and adjusting the position; the detection light path comprises an incident light path, a wide-channel light path and a narrow-channel light path; the incident light path is used for projecting a light beam and vertically projecting the light beam to a wafer to be measured; the narrow channel light path is used for collecting scattered light with the diffusion angle of [5 degrees, 24 degrees] generated on the surface of the wafer to be detected and gathering the scattered light to the narrow channel detection end, and the wide channel light path is used for collecting scattered light with the diffusion angle of [25 degrees, 70 degrees] generated on the surface of the wafer to be detected and gathering the scattered light to the wide channel detection end. According to the device for nondestructive testing of the surface of the wafer, the detection light is vertically incident, the detection light can be reflected out along the original path when the wafer is qualified, and only the defective wafer can generate scattered light, so that the wafer defect can be quickly and accurately identified. According to the wafer defect detection method, the defects of high cost, low precision and high operation difficulty of a wafer defect detection method in the prior art are overcome.

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 discloses a deep sub-wavelength scatterer particle size evaluation method based on coherent axial diffraction calculation, and belongs to the technical field of optical imaging and microstructure analysis, and the deep sub-wavelength scatterer particle size evaluation method comprises the following steps: obtaining an image, and preprocessing the image; quantifying the preprocessed image, obtaining the scattered light energy concentration of each axial position of an image surface scatterer, obtaining the attenuation condition after scattered light energy defocusing based on the scattered light energy concentration, and compensating defocusing attenuation; the method comprises the following steps: extracting a peak value position and a width of a main peak, carrying out correlation analysis on the extracted peak value position and width data of the main peak and the corresponding scatterer feature size based on a deep sub-wavelength scatterer sample with a known feature size, and constructing a peak value position mapping function and a peak width mapping function; and performing particle size evaluation based on the constructed function. According to the method, the problems of low signal-to-noise ratio, large out-of-focus interference, poor applicability and the like of a traditional method are solved, and the precision and the universality of particle size evaluation are remarkably improved.

The invention discloses a wafer detection scattered light collection objective lens, and relates to the technical field of optical imaging. The scattered light collecting lens is applied to wafer defect detection, the scattered light collecting lens sequentially comprises a first lens group, a second lens group, a third lens group and a fourth lens group from an object plane to an image plane in the optical axis direction of the lens, twelve lenses and an aperture diaphragm, and the twelve lenses and the aperture diaphragm are coaxially arranged; the first lens group is a catadioptric lens group, has positive focal power, and is used for imaging an object plane to an intermediate image plane through two times of reflection. The numerical aperture of the acquisition objective lens provided by the invention is equal to 0.9, the field of view is equal to 2.6 mm, the acquisition objective lens has the characteristics of large field of view, large numerical aperture and small center shielding, the capability of detecting scattered light of defects can be greatly improved, chromatic aberration is corrected by adopting a refraction and reflection mode, and a wider laser bandwidth can be realized compared with a general refraction mode of combining CaF2 and fused quartz.

The invention discloses a distributed polarization detection system and method based on position regulation and control target reconstruction, and belongs to the field of distributed polarization cooperative detection and photoelectronic imaging. The distributed polarization detection system comprises a lighting device, a multi-parameter auxiliary detection objective table and a long-wave infrared polarization detection device; the long-wave infrared polarization detection device is provided with three sub-polarization detection devices, the method is implemented based on a distributed polarization detection system, and polarization information in three different directions can be collected at the same time through the distributed polarization detection system based on position regulation and control target reconstruction. The identification capability of the disguised / similar target at a single angle is improved; and errors caused by time delay are avoided. Polarization information obtained by reasonably distributing detection positions is mutually supplemented, polarization images are mutually fused, target signals are effectively extracted from scattered light to analyze the polarization characteristic difference between interference light and target reflected light, and the resolution, contrast and detection distance of polarization imaging can be improved.

The invention relates to an underwater non-uniform illumination image recovery method and device based on polarization imaging, and the method integrates non-uniform illumination correction, contrast enhancement and detail improvement, and comprises the following steps: S1, carrying out the preliminary separation of backscattered light and target information light of two polarization sub-images through a low-rank sparse matrix decomposition method; s2, performing non-uniformity correction on the backscattered light from three aspects of adaptive brightness adjustment, gamma correction and local brightness homogenization; s3, fusing the backscattered light subjected to non-uniform correction according to a proportion to obtain homogenized backscattered light; and S4, according to the backscattered light after non-uniform correction, restoring the two polarization sub-images and fusing the two polarization sub-images according to a certain proportion to obtain an underwater clear image with uniform illumination. The non-uniform illumination can be effectively corrected, the overexposure phenomenon is avoided, and the image contrast and definition are improved.

The invention provides a recycled carbon fiber quality detection method based on machine vision, and the method comprises the steps: obtaining a surface image of a carbon fiber bundle through a machine vision method, and carrying out the preprocessing of the image, including image denoising and enhancement; for the preprocessed surface image of the carbon fiber bundle, extracting the morphological characteristics of the fiber bundle, including fiber bundle surface texture and fiber orientation distribution, for representing the morphological change of the fiber bundle under the reciprocating bending stress; acquiring a scattered light intensity distribution image on the surface of the carbon fiber bundle, and extracting spatial distribution characteristics of scattered light intensity through an image segmentation method, including uniformity and continuity of scattered light intensity distribution; if the fracture risk exists, positioning the identified high-risk area, and collecting image data of the high-risk area; according to the high-risk area image data, scattered light intensity distribution characteristics are extracted, a quantitative relation between scattered light intensity space distribution and the fiber bundle fracture risk is established, and a quantitative index for evaluating the fiber bundle fracture risk is obtained.

The invention discloses a roadway surrounding rock deformation monitoring method based on an optical fiber sensor, and the method comprises the steps: laying on the surface of roadway surrounding rock through employing a distributed optical fiber sensing technology, and obtaining original optical signal data; processing backscattered light data in the original optical signal data through a Brillouin optical time domain analysis algorithm, extracting frequency deviation of an optical signal, and obtaining strain distribution data; according to the strain distribution data, in combination with a pre-established surrounding rock mechanical model, performing initial inversion calculation by adopting a finite element method to obtain initial three-dimensional deformation distribution; on the basis of the initial three-dimensional deformation distribution, updating dynamic boundary conditions of the surrounding rock mechanical model by acquiring real-time geological parameter data to obtain an optimized mechanical model; carrying out inversion calculation on the strain distribution data again by adopting an optimized mechanical model to generate final three-dimensional deformation distribution; and based on the final three-dimensional deformation distribution, performing comparison judgment through a preset deformation threshold, determining the stability state of the surrounding rock, and generating an early warning signal.

The invention discloses a particle size measuring device based on combination of a dynamic light scattering method and a sedimentation method and a measuring method thereof. The particle size measuring device comprises a laser, a light intensity adjusting unit, a sample pool, a thermostatic bath, a PD detector, an optical fiber head, an APD detector, a data acquisition unit, a PC and a control unit. The laser emits incident laser, the incident laser passes through the light intensity adjusting unit, penetrates through the sample cell and a sample and then enters the PD detector, and a transmission light signal is collected through the data acquisition unit and transmitted to software for calculating the particle size and concentration of settled large particles; scattered light is received by an optical fiber head with a fixed angle of 90 degrees or 160-175 degrees and is converted into a digital signal by an APD detector, and the digital signal enters a data acquisition unit and is transmitted to software for calculating the particle size of particles in a non-settling nanometer range. According to the technical scheme provided by the invention, the particle size distribution information of the wide-distribution particle dispersion system in a nano-micron range can be measured in a testing process.

The invention discloses a dynamic geological survey system and a construction simulation method. The dynamic geological survey system comprises an intelligent sensing and data acquisition module and a multi-source data fusion processing module, the intelligent sensing and data acquisition module comprises a Raman scattering optical fiber strain sensor array, a three-component seismometer monitoring network and a distributed optical fiber pressure sensing subsystem; the Raman scattering optical fiber strain sensor array, the three-component seismometer monitoring network and the distributed optical fiber pressure sensing subsystem form a multi-dimensional sensing network for shield construction geological monitoring. By means of the integrated intelligent sensing and data acquisition module, geological changes in the shield construction process can be monitored. The Raman scattering optical fiber strain sensor array, the three-component seismometer monitoring network and the distributed optical fiber pressure sensing subsystem jointly form a multi-dimensional sensing network, geological strain, microseismic events, pore water pressure and other key information can be captured, and comprehensive geological data support is provided for construction.

The invention provides a water turbidity measurement method and system for water ecological investigation, and the method comprises the steps: determining the scattering difference characteristics of suspended particles in a to-be-detected water body to light through collecting a scattered light signal of the to-be-detected water body and a light signal of a corresponding environment background of the to-be-detected water body; determining a disturbance error of the flow velocity in the to-be-measured water body during measurement of the suspended particles; determining the turbidity gradient of the suspended particles in the to-be-detected water body based on the turbidity inversion model in combination with the scattering difference characteristics and the disturbance error; determining the viscosity state of the water body power in the to-be-detected water body, and determining the attenuation relationship between the suspended particles in the to-be-detected water body and the temperature according to the viscosity state and the fluctuation characteristics of the ambient temperature around the to-be-detected water body; and dynamically compensating the turbidity gradient of the suspended particles in the to-be-detected water body through the attenuation relationship to obtain a dynamic turbidity value of the to-be-detected water body. By adopting the scheme of the invention, the influence of multi-parameter dynamic interference on the measurement of the water turbidity in the to-be-measured water can be reduced.

The invention discloses a wafer detection focusing method and device, electronic equipment and a computer storage medium. The method comprises the following steps: when a target detection point of a to-be-detected wafer moves to an imaging center position of a detection camera, obtaining a wafer warping degree which is obtained by carrying out distance measurement on the target detection point and is corresponding to a distance measuring instrument; and controlling the detection camera to focus according to the wafer warping degree corresponding to the target detection point and the initial focal length of the detection camera, so that a to-be-detected wafer image shot by the detection camera at the target detection point meets a preset detection requirement, and the wafer detection speed and precision are improved. Meanwhile, the detection camera and the range finder are coaxial, the range finder is always located in front of the scanning path of the detection camera, an independent light path and the range finder are used for focusing, interference of irregular reflection or scattered light generated by the range finder focusing and ranging light path on an imaging light path of the detection camera is avoided, and the stability and reliability of wafer detection are improved.

The invention discloses a vision-based molded lens edge thickness detection method and a related device. The method comprises the following steps: introducing visible gas into an edge area of a molded lens to form a gas film disturbance layer; the gas film disturbance layer is excited by illumination to generate refractive index change; collecting an interferometric phase image corresponding to the scattered light intensity; carrying out Fourier transform analysis on the interference fringes and carrying out temperature correction; and finally, calculating edge thickness distribution through feature space mapping. A gas film disturbance layer is introduced to the edge of the lens to serve as a physical signal conversion bridge, and a multi-light-path interference imaging and spectrum analysis technology is matched, so that the interference problem of a transparent material in direct optical measurement can be effectively avoided, high-precision and non-contact detection on the edge thickness of the molded lens is realized, and the detection precision is improved. And meanwhile, the device has the characteristics of high environmental interference resistance and good measurement stability.

The invention provides a door and window glass defect feedback control method and device, electronic equipment and a storage medium, and relates to the technical field of door and window glass defect detection. The method comprises the steps of collecting a first image after a polarized light imaging detection device is adjusted to suppress reflected light on the surface of glass and enhance scattered light of bubbles in the glass; after the polarized light imaging detection device is adjusted to enhance reflected light on the glass surface, a second image is collected; calculating an adaptive weight group by analyzing local characteristics of the second image; weighting the first image according to the self-adaptive weight group, and subtracting the weighted first image from the second image to obtain a difference image; and extracting bubble defect information in the glass by analyzing the differential image. According to the method, interference caused by non-uniformity of glass surface reflection is overcome, the adaptability of image differential processing to surface reflection background suppression is improved, and therefore image features of internal bubble defects are extracted more effectively and more accurately.

The invention provides a method for realizing carbon fiber extraction control by using deep learning, and the method comprises the steps: obtaining a scattered light intensity matrix and an interference image of a carbon fiber component, carrying out the feature extraction of image data through combining the scattered light intensity matrix and the interference image, and obtaining a feature vector reflecting the damage state of the carbon fiber component; the extracted feature vectors are input into a pre-trained damage state evaluation model, the damage degree of the carbon fiber component is judged, and if the damage degree exceeds a preset threshold value, the carbon fiber component is marked as a to-be-recycled component; according to the damage degree of the carbon fiber component, a multi-target optimization model of pyrolysis temperature, carbon fiber decomposition rate and carbon fiber purity is constructed, and target pyrolysis furnace temperature field distribution is determined; and according to the current performance evaluation or future performance change interval of the carbon fibers, a grading recycling scheme of the carbon fibers is generated by combining the damage degree of the carbon fibers, and full-life-cycle closed-loop management of carbon fiber recycling is formed.

The invention discloses a nut defect detection method based on X-ray imaging, and particularly relates to the field of X-ray nut material internal defect imaging, which comprises the following steps: generating and adjusting an initial light beam of X-rays through a synchronous radiation source, and constructing uniform irradiation field data for nut material detection; acquiring angle scattering light intensity matrix data based on the uniform irradiation field data; and performing phase inversion and sparse constraint optimization on the angle scattering light intensity matrix data to generate electron cloud density optimization distribution data, and constructing density connectivity relation graph data based on the electron cloud density optimization distribution data. By introducing a detection principle of combining high-coherence X-ray scattering imaging based on a synchronous radiation source and electron cloud density disturbance analysis, lossless identification of an early microcosmic physical deterioration region in a nut is realized; the problem that an existing method based on absorption imaging is insufficient in defect detection capacity under the background of weak density gradient and homogeneous component is solved.

A system includes a radiation source, an optical system, an optical element, a detection system, and a processor. The radiation source is configured to generate a radiation beam. The optical system is configured to direct the radiation beam toward a target structure and to receive the scattered radiation. The target structure is configured to produce scattered radiation comprising one or more scattered beams. The optical element is configured to control a position of the one or more scattered beams. The detection system is configured to receive a portion of the position-controlled scattered radiation and to generate a detection signal. The processor is configured to determine a property of the target structure based on at least the detection signal.

The invention discloses an overhead line system cable state real-time monitoring method and sensing system based on distributed optical fiber sensing. The Mach-Zehnder interference and phi-OTDR fusion type distributed optical fiber sensing system comprises a first light source, a second light source, a Mach-Zehnder interferometer, a phi-OTDR and a data acquisition and processing module. Raman amplifiers are arranged at the two ends of the Mach-Zehnder interferometer, so that the sensing distance is prolonged; the optical fiber sensing system extracts an interference optical signal and a backward Rayleigh scattering optical signal corresponding to a fault event after phase modulation when the fault event occurs; then processing the extracted backward Rayleigh scattering light signal to obtain intensity change information of a fault event, and demodulating the position of the fault event; and sending the two-dimensional optical signal into a pre-trained Swin Transform network model to extract a time domain feature, a frequency domain feature and a spatial domain feature, and identifying the type of a fault event through a classifier.

The invention discloses a device and method for measuring dust concentration distribution at an inlet of an aero-engine, and belongs to the field of aero-engine sand swallowing tests, the device comprises a pulse laser light source, a shaping module, an optical image acquisition module and a data post-processing module, the pulse laser light source is arranged at a preset position around the aero-engine and is used for emitting laser beams, and the shaping module is used for shaping the laser beams; the aero-engine is located in a sand dust environment to be detected; the shaping module is used for receiving the laser beam and outputting a sheet-shaped beam; the optical image acquisition module is used for receiving coherent scattered light emitted by the grit in the irradiation area of the flaky light beam to form a laser speckle image, and transmitting the obtained laser speckle image to the data post-processing module; and the data post-processing module processes the laser speckle image by adopting an inlet sand dust concentration measurement algorithm to obtain the concentration distribution of the inlet sand dust of the aero-engine. The device is simple in structure, and is suitable for measuring the sand dust concentration distribution at the inlet in the sand swallowing experiments of aero-engines with different sizes or stages.

Provided in the present invention are an imaging device and method for turbid oil abrasive particles based on polarized image enhancement, which belong to the technical field of image processing. The imaging device of the present invention includes a CMOS fixing device, a Stokes polarized CMOS sensor, an optical lens sleeve and an optical magnifying glass, where the Stokes polarized CMOS sensor includes a CMOS sensor and a Stokes analyzer. By using a polarization characteristic difference between scattered light of lubricating oil media and reflected light of abrasive particles, Stokes vector information is measured in real time under turbid lubricating oil scenes, the scattered light of the media is filtered out, image quality of the abrasive particles is improved, coverage duration for monitoring abrasive particle imaging is effectively prolonged.

The invention relates to the technical field of optical particulate matter sensing, in particular to a particulate matter particle size recognition and concentration detection method. The method comprises the following steps: laser emitted by a laser forms a laser beam which is focused and then diverged through a lens; with a laser focus as a reference, at least two photosensitive devices are distributed in the light beam propagation direction and comprise a perifocus device and a far focus device, and receiving surfaces of the near focus device and the far focus device face laser beams to collect scattered light; scattered light signals of each device are collected, and are input into a processing unit after independent current / voltage conversion, signal amplification and analog-to-digital conversion; based on the characteristics that small-particle-size scattered light is preferentially captured by perifocus high irradiance and large-particle-size scattered light is preferentially captured by far focus large beam diameter, a mapping relation between particle sizes and channels is established; the number concentration and mass concentration coefficient of each channel is calibrated through standard particles, and synchronous detection of PM1.0, PM2.5 and PM10 is realized in combination with linear processing, so that the particle size recognition precision and the concentration measurement reliability are effectively improved.

The invention relates to the field of water quality parameter detection, in particular to a full-spectrum water quality multi-parameter analysis detector which comprises a full-spectrum acquisition module, a preprocessing module, an information processing module and an application module. The full-spectrum acquisition module is used for transmitting a full-spectrum signal to a detection sample, detecting transmission light and scattered light signals and generating original spectrum data; the preprocessing module is used for preprocessing the original spectrum data by adopting an edge calculation mode to obtain a standardized spectrum matrix; the information processing module is used for calculating the actual concentration value of each impurity in the detection sample according to the standardized spectrum matrix; according to the method, the influence relation between different types of impurities is introduced, compared with a common prediction method, the prediction precision of the concentration of each impurity is higher, whether early warning is needed or not is judged according to the prediction precision, and the situation of misjudgment is avoided.