1427 results about "Signal intensity" patented technology

The invention relates to the technical field of multispectral imaging, in particular to a multispectral imaging fused pattern recognition image acquisition method and device, and the method comprises the following steps: obtaining a multiband substrate response value through a multispectral sensor, generating response difference distribution through moving average filtering, inputting cross-correlation analysis, extracting a space offset vector, and compensating displacement; after the signal intensity of the mark points is captured, Gaussian fitting is carried out to generate registration coordinates, triangular mesh division is carried out, offset is calculated, interpolation mapping is carried out, a registration error distribution diagram is generated, bilinear interpolation remapping is carried out to collect time sequence parameters, and a multispectral imaging data set is output. According to the method, noise is eliminated through moving average filtering, offset vectors are extracted in a cross-correlation mode, array displacement is compensated, mark points are positioned through two-dimensional Gaussian fitting, a registration error graph is constructed through triangular meshes, parameters are collected through bilinear interpolation remapping, geometric distortion is corrected, feature consistency and collection synchronism are enhanced, and the imaging resolution ratio and the signal-to-noise ratio are improved.

The invention relates to a cooperative control method and system for realizing self-organizing protection of a multi-unmanned aerial vehicle cluster, and the method comprises the steps: M1, enabling the unmanned aerial vehicle cluster to execute a task, obtaining the data information of the remaining power, RSSI signal intensity and IMU attitude of each unmanned aerial vehicle in real time based on an airborne built-in sensor, and acquiring data information of distances and relative speeds of obstacles around the unmanned aerial vehicles in real time based on an airborne external millimeter-wave radar, constructing a dynamic threshold function stop, and if the RSSI signal strength of each unmanned aerial vehicle is greater than the stop, outputting data information of the residual electric quantity and IMU attitude of each unmanned aerial vehicle. According to the method, misjudgment (such as transient packet loss due to electromagnetic shielding) caused by temporary signal interference is effectively avoided, the misjudgment rate is reduced by 40%, unnecessary return or cluster recombination is reduced, continuous task execution is guaranteed, it is ensured that leader handover is completed quickly (at the millisecond level) when a host fails, and the situation that a cluster falls into disorder due to single-point failure is avoided.

The invention discloses a composite precipitation cloud layer identification method based on a laser radar-cloud radar, and the method comprises the steps: obtaining the observation data of the laser radar and the cloud radar, and carrying out the data matching of the observation data; processing a signal of the laser radar in a height interval of 18-20 km to obtain a preprocessed laser radar signal; performing laser radar cloud boundary identification based on a VED algorithm, and endowing different laser radar cloud scores according to the signal attenuation rate and the signal gradient; removing earth surface clutters by using a threshold method based on observation of spectral width and Doppler velocity; carrying out cloud radar significant echo recognition based on a threshold method, and determining the cloud score of the cloud radar according to different reflectivity factor signal intensities; determining a light rain area and a heavy rain area according to the Doppler velocity; cloud layer boundary information and a hairy rain area are obtained through cloud layer recognition result fusion, and cloud layer recognition and rainfall area recognition are completed; according to the invention, the accuracy of weather prediction is improved.

The invention provides a defect detection system and a defect detection method, the defect detection system comprises an objective table, an illumination channel and a plurality of detection channels, the illumination channel comprises a light source, and the light source is used for providing detection light spots for a detection area of a to-be-detected object. The detection channel comprises an objective lens and a detector, the objective lens is used for collecting scattered light generated by the detection light spot in the detection area, and the detector is used for determining the signal intensity of the scattered light so as to determine defect information of the detection area based on the signal intensity. The incident plane is perpendicular to a second plane where the optical axes of the detection channels are located, deviation angles exist between the optical axes of the detection channels and the normal direction of the surface of the to-be-detected object, and at least two deviation angles in all the deviation angles meet the angle difference condition. According to the device, scattered light of different types of defects can be efficiently collected, concave defects and convex defects can be accurately detected through a plurality of detection channels, missing detection can be avoided, and the two types of defects existing on the surface of an object to be detected can be accurately detected.

The invention relates to the technical field of sensor data fusion, in particular to a real-time dynamic attitude stability control method and system based on multi-sensor fusion, and the method comprises the following steps: collecting multi-source sensor data, and correcting to generate a synchronous sensor data set; calculating a stability coefficient, a signal quality coefficient and a consistency coefficient, weighting the signal quality coefficient and the consistency coefficient to generate a dynamic fusion weight coefficient, executing weighted fusion based on the weight, outputting a fusion attitude state estimation result through adaptive extended Kalman filtering, and generating an optimization control instruction sequence by combining with dynamic constraint model rolling optimization; according to the method, a dynamic weight mechanism based on noise and signal strength is introduced to achieve self-adaptive fusion, the synchronization precision and reliability are improved by combining consistency verification, abnormal signals are corrected through self-adaptive filtering, the attitude estimation stability is enhanced, and the performance of the system is improved. And a control instruction is generated through rolling optimization, so that rapid and accurate adjustment is realized, and attitude keeping and control consistency in a complex environment is improved.

The invention provides a bolt monitoring method and device based on electromagnetic ultrasound and a 3D phased array, and relates to the technical field of bolt monitoring. A two-stage detection process is adopted, firstly, preliminary screening is conducted through electromagnetic ultrasound, an electromagnetic ultrasound device excites ultrasonic waves and receives echo signals, and according to the relation between the intensity of the echo signals and the passing time, a 3D phased array is obtained; constructing a time-intensity curve of each detection section, and rapidly screening candidate sections with abnormal echo signals; the method comprises the following steps: performing comprehensive three-dimensional space scanning on a candidate section through a 3D phased array technology, performing accurate scanning in a three-dimensional space through focused ultrasonic waves to obtain an ultrasonic echo signal of each space point, extracting the ultrasonic echo signal intensity of each space point and calculating a standardized deviation to mark an abnormal point exceeding a set threshold value, and finally marking the abnormal point. And through spatial aggregation analysis, a plurality of abnormal points are aggregated into an abnormal region, so that the defect positioning precision is further improved.

The invention discloses an engine oil carbon deposition sampling detection method and system based on multispectral imaging, and the method comprises the steps: carrying out the collection of a to-be-processed multispectral image of an engine oil sample under a multispectral light source, and carrying out the preprocessing of the image to obtain a to-be-processed image; performing dark current correction on the to-be-processed image according to a band ratio method, and enhancing the signal intensity of the to-be-processed image; calculating the spectral reflectivity of the to-be-processed image according to the signal intensity of the to-be-processed image; extracting a three-dimensional feature tensor in the to-be-processed image according to the spectral reflectivity; segmenting the to-be-processed image according to the three-dimensional feature tensor, and screening a carbon deposition region; calculating a carbon deposition probability value of each pixel point in the carbon deposition area according to the spectral reflectivity; and setting a carbon deposition threshold value according to the carbon deposition probability value for judgment so as to judge whether carbon deposition exists in the engine oil sample or not. The similarity between the sample engine oil spectral reflectivity and the reference engine oil is reflected, and a possible carbon deposition area is found, so that the carbon deposition defect is accurately judged and identified.

The invention provides a wafer ultrasonic detection method and device, and the method comprises the steps: carrying out the global ultrasonic scanning of a whole wafer along a two-dimensional spiral path, obtaining a plurality of initial detection echo signals, forming a global echo signal group, and recording the position coordinates of the initial detection echo signals; determining a suspected bubble area based on the global echo signal group; the suspected bubble area at least has an initial measurement echo signal whose intensity is lower than a preset signal intensity threshold value; positioning the position coordinate of a suspected bubble area based on the position coordinate of the initially measured echo signal; performing local ultrasonic scanning on the suspected bubble area to obtain a plurality of retest echo signals to form a local echo signal group; judging whether bubbles exist in the suspected bubble area based on the local echo signal group and determining defect types of the bubbles; the resolution of the global ultrasonic scanning is lower than that of the local ultrasonic scanning. According to the invention, global low-resolution scanning along the spiral path and local high-resolution scanning of the wafer can be realized, and the dual advantages of efficiency and accuracy are achieved.

The invention relates to the technical field of semiconductor wafer defect detection, and discloses a semiconductor wafer defect detection method and system, and the method comprises the steps: generating a spatial staggered excitation pattern, and projecting the spatial staggered excitation pattern to the surface of a semiconductor wafer, the spatial staggered excitation pattern comprising an excited region and an unexcited region; capturing an optical image of the surface of the semiconductor wafer; according to the optical image, calculating the difference between the optical signal intensity of the excited area and the optical signal intensity of the adjacent non-excited area in the optical image; according to the difference, carrying out background deduction on the optical image so as to display a potential defect signal; and identifying the manifested potential defect signal. Therefore, the method can significantly improve the sensitivity, accuracy and efficiency of semiconductor wafer defect detection, thereby effectively improving the yield and reliability of semiconductor products, and reducing the production cost.

The invention provides a method for detecting an external vesicle marker through high-flux nano plasma exciting light immune color development, and belongs to the technical field of human extracellular vesicles. After a serum sample is subjected to centrifugal treatment, the serum sample and a CD81 capture antibody substrate are incubated, and the particle size distribution of the vesicles is monitored in real time; a zwitterionic polymer modified gold nanoparticle LAM detection probe and a polyethylene glycol modified silver nanoparticle LprG detection probe are prepared to be specifically combined with a vesicle surface antigen, a chromogenic enhancement solution is adopted to induce a plasma resonance signal, and full-hole scanning imaging is carried out; and constructing a double-layer game optimization model to cooperatively optimize the detection sensitivity and the signal stability, carrying out weighted summation on normalized signals of the particle size subgroups to obtain comprehensive detection signal intensity, comparing the comprehensive detection signal intensity with a threshold value, and outputting a final judgment result. The technical problem that quantitative accuracy is affected by signal intensity deviation caused by vesicle particle size difference in outer vesicle marker detection is solved.

The invention provides a real-time estimation method and system for a small-target radar adaptive signal-to-noise ratio. According to the method, a motion model is established based on a historical trajectory of a maneuvering target, and a dynamic position prediction sequence is generated; acquiring a scanning beam pointing angle sequence and a timestamp echo signal intensity sequence; starting multiple rounds of iterative detection for each target position point in the prediction sequence, and shrinking a detection window bidirectionally until the boundary is smaller than the width of a beam half-power point; a signal intensity peak value and background noise intensity in a final iteration window are extracted, a beam irradiation efficiency factor is generated in combination with the spatial matching degree of the scanning beam directional angle sequence and the position prediction sequence, and a signal-to-noise ratio dynamic correction is cooperatively calculated; and weighting and fusing the correction, the signal peak value and the noise intensity, and outputting a final signal-to-noise ratio value of the maneuvering target in real time. According to the invention, the signal-to-noise ratio real-time estimation precision and stability of a small target radar when a high-speed maneuvering target passes through a beam edge are improved.

The invention discloses a diamond low-frequency current measurement method with nonlinear response to magnetic field intensity, which is characterized in that two coils are wound on a magnetic flux collector with a communicated structure, a high-frequency (800Hz) high-voltage (7V) driving current is injected into one of the coils, a magnetic field generated by the coil is amplified through the magnetic flux collector and guided to an area where an NV color center magnetometer is located, and the NV color center magnetometer is located; and the signal is driven to enter a nonlinear response interval in the demodulated ODMR spectrum. A weak (1-50mV) to-be-measured low-frequency (0.1-10Hz) current signal is injected into the other coil, amplitude modulation is performed on the weak (1-50mV) to-be-measured low-frequency (0.1-10Hz) current signal by using the same frequency as the driving current, and the weak (1-50mV) to-be-measured low-frequency (0.1-10Hz) current signal is amplified by the magnetic flux collector and guided to the NV The microwave frequency is locked at the maximum slope point of the ODMR frequency spectrum through CW-ODMR phase-locked amplification, so that the relationship between the change of the red fluorescence signal intensity and the size of the external magnetic field is obtained, and the signal intensity of the low-frequency current magnetic field to be measured is measured according to the relationship.

The invention provides a tumor cell assisted positioning system and method based on a composite image, and relates to the technical field of medical image.The system comprises a data acquisition module used for synchronously acquiring radio frequency echo signals, ultrasonic images and computed tomography data of target biological tissue to generate an original fusion data set; the feature processing module is used for performing spatial registration and feature extraction on the original fusion data set to obtain a multi-dimensional feature set; and the identification imaging module is used for extracting a multi-band radio frequency echo signal intensity level value of the target area based on the multi-dimensional feature set, generating a tissue radio frequency characteristic diagram through logarithmic compression, and performing pixel-level fusion on the tissue radio frequency characteristic diagram and the synchronous ultrasonic image to generate a composite image. According to the method, the three-dimensional coordinates of the tumor boundary are determined through multi-modal data fusion and precise calibration in combination with anatomical structure constraints, and the accuracy of tumor cell positioning is improved.

The present disclosure relates to digital watermarking systems that may use visual masks to optimize watermark embedding in digital imagery. A visual mask provides guidance for adjusting digital watermark signal strength, enabling improved trade-offs between watermark imperceptibility and robustness. Multiple embodiments generate visual masks including: (1) a Perceptual Modeling Candidate approach using contrast masking and texture classification based on standard deviation mapping; (2) a wavelet-based approach using Dual-Tree Complex Wavelet Transform for translation-invariant frequency analysis; (3) artificial intelligence approaches employing convolutional neural networks trained to optimize embedding strength while minimizing perceptual distance metrics such as LPIPS; and (4) LPIPS threshold masking that determines optimal embedding strengths by testing multiple candidate strengths. Visual masks enable content-adaptive digital watermarking that places stronger signals in textured regions while maintaining imperceptibility in flat regions, improving visibility-robustness performance compared to uniform embedding approaches.

The invention discloses an indoor and outdoor navigation method, device and equipment, and relates to the technical field of computers. The method is applied to an edge device, the edge device is carried on a robot, and the method comprises the steps that after it is detected that the robot is started outdoors, a first planned path is generated based on the initial position of the robot, an outdoor offline map and the indoor entrance position; when it is detected that the intensity of the entrance marker and the GPS signal at the indoor entrance position is smaller than an intensity threshold value, an indoor navigation mode is triggered; constructing an indoor coordinate system by taking the indoor entrance position as an original point; indoor motion data of the robot and image data of the environment where the robot is located are obtained through an inertial measurement unit and image acquisition equipment; determining a current indoor coordinate of the robot based on the indoor map, the indoor motion data and the image data; and generating a second planning path based on the indoor coordinate system, the current indoor coordinate and the target task point. According to the scheme, the navigation efficiency can be improved.

The invention discloses a spiral resonance photoacoustic cell and an operation method, the spiral resonance photoacoustic cell comprises a gas chamber straight tube, a spiral tube, an optical fiber collimator and an optical fiber F-P sonic sensor, the two ends of the gas chamber straight tube are open, the two ends of the spiral tube are communicated with the gas chamber straight tube, an acoustic resonance point is formed at the center of the spiral tube, and the optical fiber F-P sonic sensor is arranged in the central area of the spiral tube; and the optical fiber collimator is arranged at one end of the air chamber straight pipe. The spiral pipe is wound outside the air chamber straight pipe, the spiral pipe is communicated with the air chamber straight pipe, the structural design of the spiral pipe enables the spiral pipe to form acoustic resonance at a specific frequency, and the optical fiber F-P sonic sensor obtains a photoacoustic signal; compared with a conventional resonance photoacoustic cell, the physical volume of the resonance photoacoustic cell is greatly compressed, and the system integration level is effectively improved. More importantly, under the condition that a compact appearance similar to that of a non-resonant photoacoustic cell is kept, the device amplifies the photoacoustic signal intensity by several times through an acoustic resonance effect, and the detection sensitivity and the signal-to-noise ratio of the system are remarkably improved.

The invention discloses a multi-signal-source scene-oriented generative radio map collaborative estimation method, which comprises the following steps of: S1, sampling received signal strength of a plurality of users on a plurality of frequencies to construct a matrix form, and decomposing by adopting an NMF matrix decomposition method to obtain an NMF matrix; each decomposed received signal strength component corresponds to an independent signal source; s2, constructing and training a radio map inference model of a single signal source; and S3, for each received signal strength component obtained by decomposition in the step S1, estimating correspondence by using a radio map reasoning model of a single signal source. According to the method, the signal intensity components corresponding to multiple signal sources are decomposed by adopting the matrix decomposition theory, and the neural network is trained by utilizing the learning algorithm based on the GAN, so that the accuracy and generalization ability of the system are improved. The method can effectively work under the condition that geographic data is inaccurate or matrix decomposition results have errors.

The invention discloses an atmospheric aerosol detection method and system based on a dual-angle light scattering signal, and relates to the technical field of environment monitoring. The method comprises the steps that forward scattering signals and lateral scattering signals generated by particles to be detected in atmospheric aerosol conveyed into a detection area under laser irradiation are obtained, and environmental parameters of the atmospheric aerosol are obtained, specifically, the environmental parameters comprise at least one of the temperature value and the humidity value; and calculating a signal intensity ratio of the forward scattering signal to the lateral scattering signal of the to-be-detected particle, and inputting the signal intensity ratio of the to-be-detected particle, the forward scattering signal, the lateral scattering signal and the environmental parameters into a pre-trained particle size identification model to obtain a particle size value of the to-be-detected particle output by the particle size identification model. According to the scheme, the particle size detection precision of the particles in the atmospheric aerosol can be improved.

The invention relates to the technical field of laser radar signal processing, and discloses a laser radar echo signal processing method. The method comprises the following steps: acquiring an original echo signal sequence of a plurality of scanning periods, wherein the sequence comprises signal intensity data of all detection channels at each timestamp; comparing the signal intensity change mode of each detection channel in each scanning period with the signal intensity change mode of all detection channels in all scanning periods, and extracting the signal fluctuation index of each detection channel in each scanning period; analyzing a signal intensity distribution interval and a signal fluctuation index of each detection channel in each scanning period, and generating a signal dynamic variation; then comparing signal space distribution characteristics of each detection channel and all the rest detection channels in each scanning period and signal intensity gradient differences of adjacent channels, and extracting a space correlation difference; and fusing the signal dynamic variation of all the detection channels and the spatial correlation difference to generate a signal quality evaluation value of each scanning period.

The invention discloses a preparation method and application of a photo-thermal biosensor for tumor cell quantification and vitality dual-index liquid biopsy. Phosphatidylserine (PS) is exposed by enriching and cracking tumor cells, is identified and combined by an aptamer Apt2, and is driven to be separated from Apt2-Cu2-xTe NSs; after magnetic separation, separated supernatant is subjected to photo-thermal detection; the photo-thermal signal intensity is positively correlated with the number of cells, so that quantitative detection is realized; during cell apoptosis, PS is turned out of the membrane, Apt2-Cu2-xTe NSs is combined with the surface of the membrane, separated supernatant is subjected to photo-thermal detection after magnetic separation, and the photo-thermal signal enhancement amplitude is in negative correlation with cell activity. The platform has the advantages of POCT characteristics, low cost and portability, and a new tool is provided for precise tumor diagnosis and treatment.

The invention provides a deep hole drilling numerical control correction method and system based on force sense feedback, and relates to the technical field of machining numerical control, and the method comprises the steps: monitoring the vibration amplitude and frequency spectrum features of the surface of a drill rod, comparing the vibration amplitude and frequency spectrum features with a cutting vibration feature library, and extracting a chip attachment signal strength index; fusing the index with a resultant force time domain signal to generate a data pair, and separating an additional load time domain sequence from a pure cutting force time domain sequence by using an interference stripping algorithm; if the additional load time domain sequence exceeds the threshold value, a cleaning signal is issued, and cuttings are discharged; comparing the pure cutting force time domain sequence with a corresponding reference, calculating a force deviation, and generating a compensation instruction according to a feed compensation strategy; the instruction is executed, machining continues, the hole diameter and guiding deviation are fed back, the correction effect is verified, and parameters are adjusted till the machining precision is met, so that chip accumulation can be accurately recognized, cleaning is triggered, the real cutting force and the additional interference load are effectively separated, the feeding parameters are dynamically compensated, and the deep hole machining precision and stability are remarkably improved.

The invention discloses a clinical examination equipment remote calibration method and system based on edge calculation, and relates to the field of instrument calibration, the system is composed of a plurality of functional modules, and the system comprises: a multi-modal data acquisition module for acquiring historical calibration data of absorbance, including fluorescence images, cell fluorescence signal intensity and morphological characteristics; the edge calculation module is used for establishing a multiple linear regression model according to historical calibration data of the absorbance and predicting an attenuation curve of the optical detection unit; on the basis of a federated learning framework, a fluorescence signal intensity compensation matrix is optimized by utilizing shared parameters among edge nodes, and light path gain parameters are automatically adjusted; performing outlier analysis on each batch of detection data through a built-in Westgard rule engine, and triggering automatic redetection of morphological characteristics; analyzing absorbance time sequence data in combination with a 1D-CNN model, and identifying reagent pollution and optical assembly aging; and the drifting calibration module adopts a PID controller to dynamically adjust the power of the laser.

The invention relates to the technical field of defect detection, and discloses a laser radar defect identification method and system based on visual inspection, and the method comprises the steps: collecting an original scattering image of the surface of equipment, carrying out the denoising, and enhancing the details, and obtaining a clear scattering image; obtaining signal intensity distribution diagrams corresponding to the multiple alternative light wavelengths, analyzing the signal intensity distribution diagrams, and determining a target light wavelength; performing iterative optimization on the target optical wavelength to obtain an optical wavelength parameter; re-collecting a scattering image on the surface of the equipment to obtain a re-collected scattering image, and carrying out secondary detail enhancement on the re-collected scattering image to obtain an enhanced scattering image; generating a scattering intensity curve according to the enhanced scattering image, and performing standardization processing to obtain a standard distribution result; obtaining defect position shape data according to the standard distribution result; and matching the defect position shape data with a preset defect library, and processing parameters to obtain defect identification data. The method can realize high-precision positioning of tiny defects.

An optical reception device includes: a reception circuit that performs digital coherent reception of an optical signal to which a probabilistic constellation shaping (PCS) is applied; a conversion circuit that samples an electric field signal in an analog format that represents an optical electric field component of the optical signal and converts the electric field signal into a digital signal in a digital format; a detection circuit that detects a sampling phase of the digital signal and generates sampling phase information that corresponds to the sampling phase; a compensation circuit that compensates for the sampling phase of the digital signal based on the sampling phase information; and an adjustment circuit that adjusts signal intensity of the digital signal before the sampling phase information is generated.

The invention discloses an ionospheric scintillation monitoring method based on a lightweight GNSS receiver, which belongs to the technical field of navigation, and comprises the following steps: extracting data through a lightweight GNSS receiver board card, carrying out detrending processing on signal intensity and carrier phase measurement values, calculating a scintillation index and adjusting parameters according to user requirements, and recording scintillation data according to a threshold value. Flicker types are distinguished through interference identification, and regional networking monitoring and visualization are realized through a cloud server; according to the ionospheric scintillation monitoring method based on the lightweight GNSS receiver, flexible monitoring, accurate identification, regional collaboration and data full-period service are realized, and the flexibility, accuracy and data value of ionospheric scintillation monitoring are effectively improved.

The present technology relates to a systems for quantifying rheotaxis in a sperm-containing sample. The system includes a microfluidic system having an inlet for charging fluids into a passage. One or more probes defining a confinement region suitable for retaining motile sperm are within the passage. The system further comprises an image processing computing device for obtaining a sequence of images of the confinement region of at least one of the one or more probes having motile sperm retained therein. The sequence of images of the confinement region is processed to determine a signal intensity value for said sequence of images, wherein said signal intensity value is based on a concentration of the motile sperm located in the confinement region at the flow rate. A rheotaxis quality value is determined for said sperm-containing sample based on the signal intensity value. Methods for quantifying rheotaxis in a sperm-containing sample are also disclosed.

The invention discloses an automatic target tracking method and system based on satellite laser ranging echo signals, and the method comprises the steps: S1, carrying out the space scanning of an uncertain domain of a ranging target through employing a regular hexagon dense scanning strategy, and completing the searching and capturing of the target; s2, after the target is captured, correcting the direction of the telescope by dynamically switching a global optimization mode and a local optimization mode by adopting a miss distance optimization method combining a Bayesian optimization algorithm and a local optimization algorithm, so as to complete the optimization of the miss distance; s3, target tracking is carried out based on the optimized miss distance, and echo signal intensity is monitored in real time; and S4, judging whether the signal is attenuated or not, re-triggering the miss distance optimization process when detecting that the signal is attenuated, and otherwise, maintaining the current tracking state.

The application discloses a two-dimensional magnetophoresis separation and detection method and system based on weight distribution, and belongs to the field of biochemical analysis. Based on the designed microfluidic chip, the physical property difference between the non-magnetic material and the magnetic material is utilized, the motion difference thereof in the magnetic field is taken as the distinguishing feature, deep-level signal exploration and analysis based on microbead quantification are realized, the number of the compound after the immune reaction and the motion difference in the magnetic field environment are utilized, force analysis calculation and physical field simulation are carried out, different weights are given to the classified signal probes, the signal strength is more accurately revealed, the two-dimensional magnetophoresis analysis method is combined, and the sensitivity and resolution capability of the analysis are effectively enhanced. In addition, the reaction time of the method is short, the operation steps are few, the multiple modes are optional, the scene applicability is strong, and the circulation use can be realized.

The invention discloses a visibility inversion method and device of a laser radar, equipment and a storage medium, and relates to the technical field of laser, and the method comprises the steps: determining a detection range boundary based on a laser radar voltage value and a preset threshold value; synchronously measuring the visibility in a segmented manner by using a ground single-point measurement visibility meter and a laser radar visibility meter, and performing inversion to obtain a function value; constructing a joint relation model by combining a laser radar equation according to the average error of the function value and the radar measurement signal, and generating a parameter mapping relation lookup table; acquiring signal intensity by means of a near-field visibility measuring device, and determining a target laser radar ratio and an extinction coefficient through the look-up table; and finally, resolving an extinction coefficient profile and inverting a visibility profile by adopting a Fernald inversion algorithm in combination with the laser echo signal path, the target extinction coefficient and the laser radar ratio. The efficiency of laser radar visibility inversion is improved.

The invention is suitable for the technical field of intelligent equipment, and provides a hearing loss risk assessment method and system, intelligent equipment and a storage medium, and the method comprises the steps: a near-ear wearable device collects an audio signal through a configured acoustic sensor, carries out the sound source classification marking of the audio signal based on a current working mode, and carries out the sound source classification marking of the audio signal; and according to a set time interval or a trigger condition, counting a signal intensity mean value of each sound source type audio signal, sending a sound source classification mark and the counted signal intensity mean value to a cloud server corresponding to the user, and indicating the cloud server to carry out hearing loss risk assessment on the user according to the sound source classification mark and the counted signal intensity mean value. The hearing loss risk assessment method and device can effectively improve the convenience, accuracy and universality of hearing loss risk assessment.