2490 results about "Signal intensity" patented technology

The invention provides a thin film surface defect detection method and system, and relates to the technical field of defect detection.According to the thin film surface defect detection method and system, an intelligent secondary verification link is constructed by introducing a defect confidence evaluation mechanism based on form and energy distribution, so that the detection performance is fundamentally improved; according to the mechanism, real physical defects with regular forms and concentrated energy and pseudo defects caused by electromagnetic interference, instantaneous film wrinkles and the like can be accurately distinguished, and the problem of high false alarm rate caused by dependence on single signal strength in the prior art is effectively solved while the high detection rate of low-contrast defects is reserved; besides, the judgment model based on physical characteristics has natural robustness for background noise generated in high-speed motion, and an adjustable confidence threshold value endows the system with extremely high practical flexibility, so that the system can adapt to complex and changeable industrial environments and different quality control standards, and the method is suitable for large-scale popularization and application. And the accuracy, the reliability and the intelligent level of the whole detection system are obviously enhanced.

The invention belongs to the technical field of path planning of unmanned equipment, and relates to a medical rescue unmanned aerial vehicle and robot dog cooperative linkage method, which comprises the following steps: integrating LiDAR point cloud, visual images, IMU inertial data and compensated UWB positioning data into a multi-modal data stream subjected to space-time alignment through time alignment and space alignment technologies; respectively extracting LiDAR and visual feature poses through parallel SLAM (Simultaneous Localization and Mapping) calculation, and carrying out graph optimization and joint optimization by utilizing a GTSAM library, so as to construct a globally optimized pose and a global semantic map; the path planning algorithm provides dynamic channel routing for the unmanned aerial vehicle and the robot dog based on a global semantic map, the feature fusion weight is adjusted by considering the environment illumination intensity and the point cloud density, the reverse iris control mechanism detects whether the robot dog enters a shielding area through a UWB signal intensity attenuation value, the unmanned aerial vehicle is switched to a UWB signal follower, and the UWB signal follower is switched to the unmanned aerial vehicle. And through combination with a Kalman filter, penetration positioning in a shielding area is realized, so that stable execution of a rescue task in a complex environment is ensured.

A transmission tower deformation monitoring device based on a phased array radar technology relates to the field of irregular contour metering, and comprises a map construction module used for constructing a regional digital map; the boundary determination module is used for near-field region boundaries; the signal acquisition module is used for acquiring a near-field echo signal of a near-field region through a narrow beam and acquiring a far-field echo signal of a far-field region through a wide beam; the calibration table construction module is used for constructing a signal intensity comparison table; the data processing module is used for determining effective monitoring data; the error calculation module is used for performing error calculation on the effective monitoring data to obtain a phase error and an amplitude error; and the parameter determination module is used for determining iron tower deformation parameters. According to the invention, the accuracy of transmission tower deformation monitoring can be improved.

The invention relates to the technical field of stone structure ultrasonic detection, in particular to a stone structure building detection method based on a concrete ultrasonic fault detection scanner, and the method comprises the steps: obtaining the initial signal intensity when an ultrasonic signal is transmitted by using the ultrasonic fault detection scanner; obtaining an ultrasonic reflection signal after the ultrasonic signal is reflected at each reflection point under each scanning layer, the intensity of the reflection signal after reflection, and the signal propagation duration; the method comprises the following steps of: obtaining a signal propagation time difference, a signal intensity difference, a signal difference index, a signal disorder degree, a defect evaluation coefficient, a seam recognition degree and a seam correction coefficient of each reflection point under each scanning layer, correcting the intensity of a reflection signal, performing three-dimensional reconstruction on a constructed tomography graph, and detecting internal defects of a stone structure building. According to the method, the interference of the reflection points on the splicing seams during stone splicing is reduced, the accuracy of detecting the internal defects of the stone structure building is improved, and the stability detection of the stone structure building is improved.

The invention, which relates to the technical field of image identification processing, discloses an AI-based image identification detection system comprising the following components: an optical physical model processing module, an environmental factor perception and analysis module, a color deviation correction module, a micro-feature enhancement module, an AI image identification module and a data storage and dynamic update module. By combining the optical physical model and the micro-feature enhancement algorithm based on the physical principle, the accuracy and reliability of object recognition under complex weather and illumination conditions are remarkably improved, and by introducing the optical physical model, the interaction between light and the object surface under different environments is accurately simulated, so that the object recognition accuracy and reliability are improved. And meanwhile, the micro-feature enhancement algorithm is optimally designed for specific environments such as low illumination and strong wind, so that the signal strength of the micro-feature region is effectively enhanced, and micro-feature deformation caused by environmental factors is recovered.

The invention relates to the technical field of unmanned aerial vehicles, and particularly discloses an unmanned aerial vehicle millimeter wave radar detection system and method and an unmanned aerial vehicle, and the system comprises a millimeter wave radar module which is used for executing multiple detection tasks and detecting the distance, speed and angle information of a target object, and has the functions of beam scanning and signal transmitting and receiving; the signal processing module is used for processing the received radar echo signal, performing target object detection and positioning through signal analysis, and generating a target positioning result; the target tracking module is used for tracking the target according to the target positioning result and the sensor data of the unmanned aerial vehicle; the method improves the signal intensity and detection distance in different detection environments by optimizing the direction and focusing of radar beams in real time, effectively eliminates noise interference through the Kalman filtering and particle filtering technology, accurately estimates the distance, speed and angle information of a target, and improves the detection accuracy through combining a deep learning algorithm and an adaptive filtering strategy. And processing details of the radar echo signals are dynamically optimized.

The invention discloses a vehicle-mounted holder laser telemetering scanning type gas leakage positioning system, and relates to the technical field of gas leakage monitoring. The vehicle-mounted pan-tilt laser telemetering scanning type gas leakage positioning system comprises a data acquisition unit for acquiring laser absorption second harmonic signal intensity of an inspection vehicle on a set route; the concentration inversion processing unit is used for inverting the gas concentration on the basis of the signal; the concentration analysis unit is used for identifying an abnormal inspection point by comparing the concentration change rate; the leakage direction analysis unit is used for predicting the leakage direction by combining wind direction concentration data; according to the invention, a signal saturation upper limit value and an optical path length value are introduced to carry out normalization processing, concentration inversion calibration is carried out in combination with a gas absorption coefficient, independent calculation is carried out at each inspection position point, and the accuracy of the inspection is greatly improved by combining remote measurement concentration distribution data, image data and a leakage position analysis unit for accurately positioning a leakage point in combination with a gas diffusion model. And continuous, dynamic and high-precision concentration distribution reconstruction in space is realized.

The invention provides a blood glucose monitoring and early warning method. The blood glucose monitoring and early warning method comprises the steps of a, collecting a skin surface spectral signal I (lambda), b, collecting skin surface temperature T, humidity H, environment light intensity L and environment electromagnetic interference E parameters, c, preprocessing the spectral signal I (lambda), removing noise N (I) through wavelet transform, and d, calculating the blood glucose monitoring and early warning parameters. And the signal intensity is corrected through an ambient light intensity compensation model. According to the blood glucose monitoring and early warning method, a non-invasive acquisition mode combining near infrared spectrum and visible light spectrum is adopted, and a multi-modal regression model and a dynamic interference compensation technology are innovatively introduced, so that the problem that the precision of a sensor is influenced by skin temperature, humidity and environmental electromagnetic interference in the prior art is solved; the timeliness and the stability of signal purification are improved by utilizing preprocessing and optimization algorithms of spectral signals, such as wavelet transform, empirical mode decomposition and fast Fourier transform.

The invention discloses a multi-scene positioning and intelligent warning system and method for industrial equipment, and the system comprises a track analysis module which obtains the radar signal data of the industrial equipment, carries out the denoising, extracts a signal intensity change feature, and generates a human body dynamic track when the matching degree of the feature and a preset metal reflection model exceeds a threshold value; the abnormity judgment module is used for acquiring the vibration sensing data of the key position, generating a vibration frequency spectrum by applying wavelet decomposition, and generating abnormal vibration alarm information if the vibration frequency spectrum exceeds a range; the intrusion alarm module is used for acquiring node signal sources, performing weighted fusion to obtain an initial positioning coordinate group, inputting the initial positioning coordinate group into a three-dimensional map model, obtaining a final coordinate result through multi-source fusion, and sending out intrusion alarm information if the result falls into a dangerous fence boundary; and the safety evaluation module is used for performing time alignment and deep fusion on the human body dynamic track, the abnormal vibration alarm information and the intrusion alarm information to generate a safety evaluation report. According to the invention, omnibearing safety monitoring and management of industrial equipment are realized.

The invention relates to the technical field of medical rehabilitation training, in particular to an intelligent hand training method and system, electronic equipment and a storage medium, and the method comprises the steps: receiving a training mode instruction selected by a user; real-time biomechanical data of the affected side hand are collected through a multi-source sensor array, the real-time biomechanical data comprise finger joint angles, electromyographic signal intensity and a touch pressure distribution matrix, and when the affected side hand is in a mirror image training mode, the six-degree-of-freedom motion trail of the uninjured side hand is synchronously collected; calling a corresponding algorithm model for processing based on the training mode, and generating a control instruction set containing pneumatic pressure parameters, electrical stimulation waveforms and virtual interaction instructions; the control instruction set is sent to a server side, a mechanical glove arranged on the hand of the affected side in a sleeving mode executes corresponding pneumatic-electric combined driving operation, and multi-sense feedback is synchronously presented. According to the application, the composite requirements of patients in different rehabilitation stages on training mode diversity, control accuracy and interactive immersion can be met.

The invention relates to the technical field of new energy power plant construction data processing, in particular to a construction site personnel track recognition system based on a two-dimensional code, which adopts laser etching to dynamically encrypt a two-dimensional code label, and improves the weather resistance of the label in a salt fog environment through a salt-dredging nano coating and antistatic packaging. And a double-fixing structure combining the elastic binding band and the magnetic fastener is suitable for high-strength operation scenes. Industrial-grade scanning base stations are deployed in a construction area in a gridding mode, three-dimensional coordinate data are captured through a multi-base-station cooperative scanning mechanism, high-reflection interference of photovoltaic panels is eliminated through a signal intensity difference algorithm, and a de-noising coordinate set is generated. The closed-loop calibration module corrects scanning angle offset and earth surface reflection weight parameters through a three-level check link, the environment adaptation module triggers an ultrasonic multi-frequency cleaning program to maintain optical performance, and the cooperative control unit adjusts the light supplementing intensity and the data fusion proportion in a linkage mode. Accurate identification of personnel tracks and multi-working-plane dynamic management and control in a complex environment are realized.

The invention discloses a substation unmanned aerial vehicle middle and low altitude automatic flight patrol safety management and control method, and relates to the technical field of intelligent operation and maintenance of power system equipment, and the method comprises the steps: setting a plurality of micro radar signal sources in a substation, and testing the signal intensity of a wireless communication system; dividing an interference area through the three-dimensional model of the transformer substation, recording the coordinates of the area causing the abnormity of the unmanned aerial vehicle equipment, and setting the area as a flight forbidden area; and generating an unmanned aerial vehicle flight path based on the transformer substation three-dimensional model, and setting a corresponding flight height and an electrified equipment distance according to different voltage class sites. According to the invention, double-AP module distributed deployment and multi-direction obstacle avoidance module configuration are adopted, so that the reliability of a communication link and the flight safety are guaranteed; based on interference area identification and differentiated parameter setting of a three-dimensional model, a precise control mechanism for different voltage levels is established, and the reliability and operation efficiency of automatic inspection of the unmanned aerial vehicle are improved.

The invention provides an AI-based passive radar multi-source electromagnetic positioning matching method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: firstly obtaining a multi-source electromagnetic signal data set of a target region, the multi-source electromagnetic signal data set is electromagnetic radiation signals synchronously captured by a plurality of signal collection devices in a preset time window, and the electromagnetic radiation signals are acquired by a plurality of signal collection devices; secondly, performing feature extraction on the multi-source electromagnetic signal data set to obtain a signal feature set containing signal intensity distribution, frequency domain correlation and time-space correlation features, then fusing the signal feature set based on a dynamic weight distribution strategy to generate a multi-dimensional positioning feature set, and then calling an AI positioning matching model to analyze positioning parameters to obtain a multi-dimensional positioning feature set; and obtaining a spatial position and a signal propagation parameter of the target electromagnetic radiation source. And finally, a positioning optimization instruction is generated according to the parameters and is fed back to the signal acquisition device cluster for parameter calibration, so that the electromagnetic positioning precision and reliability can be improved.

The invention discloses a high-sensitivity metal micro-strain sensor label and a detection method thereof, which are applied to the field of nondestructive testing and the field of structural health monitoring. The problems that an existing tag antenna is low in strain detection sensitivity and difficult in micro-strain detection are solved. The high-sensitivity metal micro-strain RFID sensing tag is attached to the surface of a component, when the tag deforms, the impedance change of the tag is Zsened, and the radar cross section changes accordingly; the reader can remotely monitor antenna parameters according to the change of the RCS0, the RCS1 and the intensity while communicating with the tag, so that the change of the intensity RSSI of an echo signal is deduced, and the deformation of the tag is indirectly known; when the impedance of the tag antenna changes, the resonant frequency of the tag changes accordingly, and the deformation information of the tag can be indirectly obtained by analyzing the deviation of the resonant frequency.

The invention is applied to the technical field of low-light image enhancement, and particularly discloses a low-light image enhancement method based on multi-scale perception enhancement structure block decomposition, which comprises the following steps: firstly, carrying out SPD decomposition on a low-illumination image to obtain four components including perception gain, signal intensity, signal structure and average intensity; a perception gain component, a signal intensity component, a signal structure component and an average intensity component are respectively enhanced through an artificially set enhancement strategy, and the four enhanced components are fused into one image again through a multi-scale framework. According to the low-light image enhancement method based on multi-scale perception enhancement structure block decomposition, the image is subjected to adjustment enhancement after being decomposed so as to generate a result with rich information and vivid perception, a synthesized multi-exposure image is obtained by adopting simple logarithm stretching, the enhancement performance can be further improved, the enhanced image is more natural and real, and the image quality is improved. The method has advantages and effectiveness in the aspects of keeping detail information and keeping image consistency.

The invention relates to a coal pulverizing system fine control method based on pulverized coal flow characteristics. The method comprises the following steps: firstly, acquiring an original sound wave signal in the flowing process of pulverized coal, and performing spectral decomposition and feature extraction adjustment on the original sound wave signal to obtain a real-time change trend of pulverized coal fineness distribution; then obtaining the electrified signal intensity of the pulverized coal particles and combining with the real-time change trend for analysis to obtain an accurate measurement value of the pulverized coal flow velocity; then, inputting the real-time change trend and the accurate measurement value of the pulverized coal flow velocity into a particle kinematics model, and calculating to obtain a dynamic estimation value of the pulverized coal concentration; the real-time change trend, the accurate measurement value of the pulverized coal flow velocity and the dynamic estimation value of the pulverized coal concentration are fused, and comprehensive monitoring parameters of pulverized coal flow are generated; and finally, dynamically adjusting a control instruction in the powder making process according to the comprehensive monitoring parameters, and finally obtaining multi-parameter monitoring data. The powder making efficiency and powder making refinement are effectively improved, and the stability and high efficiency of operation of a powder making system are guaranteed.

The invention discloses a multi-state wireless network signal dynamic imaging system and method based on meta universe, and relates to the technical field of wireless communication. According to the method, a spatial dimension prediction model and a time dimension prediction model are combined, and spatial distribution of wireless network signals is accurately predicted through a data fusion technology; the reliability and the accuracy of wireless network signals are improved by dynamically adjusting a reference weight optimization prediction result; according to the invention, by collecting the real-time network requirements of the user including the video traffic and the file uploading and downloading and the real-time requirements of the user on the wireless network signal quality, intelligent and dynamic network signal quality evaluation can be realized, and the network quality in different use scenes can meet the personalized requirements; through the signal intensity heat map and sound prompt, a user can timely obtain feedback related to wireless network signal quality, and the user is helped to find an area with the best signal in a complex environment, so that more optimized network experience is realized.

The invention discloses a shopping cart positioning method and device, and the method comprises the steps: employing an inertial navigation positioning mode to position a shopping cart when the shopping cart is not in the coverage range of a current base station; in the inertial navigation positioning process, the signal intensity of surrounding electronic price tags is obtained, and if the electronic price tag positioning condition is met, the shopping cart is positioned in a signal intensity weight calculation mode; if the scanning commodity identifier positioning condition is satisfied, positioning the shopping cart by scanning the commodity identifier to position the position of the commodity; correcting the inertial navigation positioning result based on an electronic price tag positioning result or a scanned commodity identifier positioning result of the shopping cart to obtain a first corrected positioning result of the shopping cart; and according to the first correction positioning result and a set of path points pre-generated based on a supermarket map, matching to obtain a position of the path point closest to the first correction positioning result as a second correction positioning result of the shopping cart. The precision of shopping cart positioning can be improved.

The invention provides an underground space electromagnetic positioning method and device based on track time sequence analysis, and relates to the technical field of positioning. The method comprises the following steps: acquiring an electromagnetic field phase difference and magnetic field signal intensity of a to-be-positioned target, and constructing time sequence input data according to the electromagnetic field phase difference and the magnetic field signal intensity; inputting the time sequence input data into the constructed time sequence electromagnetic positioning model; wherein the time sequence electromagnetic positioning model comprises a screening door, a sensing door and a repositioning door; and outputting target pose information in real time according to the time sequence input data and the time sequence electromagnetic positioning model. Target positioning information is autonomously sensed and captured through the time sequence electromagnetic positioning network model, and high-precision real-time continuous positioning of the moving target is achieved.

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 provides a nuclear magnetic resonance and image intelligent bimodal unfrozen water dynamic identification method and system, and belongs to the technical field of frozen soil engineering and geophysical exploration, and the method comprises the steps: sealing a frozen soil sample in a nuclear magnetic sample tube, and achieving the gradient cooling of the sample in a preset low temperature range through temperature control; scanning by using a nuclear magnetic resonance technology to obtain transverse relaxation time T2 spectrums and nuclear magnetic images of the frozen soil sample at different temperature nodes; after image preprocessing is carried out on the nuclear magnetic image, a temperature-signal intensity curve in the nuclear magnetic image is automatically extracted by utilizing an image recognition technology; carrying out integral calculation on a liquid water signal in the T2 spectrum, and dynamically calculating the content of the unfrozen water at each temperature based on a nuclear magnetic signal intensity formula; according to the method, a pore-fracture co-evolution matrix is constructed, accurate analysis of unfrozen water dynamic and pore evolution in the freezing and thawing process is realized, the method is suitable for hydrothermal coupling characteristic analysis of Qinghai-Tibet soil in a complex freezing and thawing environment, and reliable technical support is provided for stability evaluation of frozen soil engineering.

The invention provides an unmanned aerial vehicle-based high-rise hyperbolic glass curtain wall automatic inspection method and system, and the system comprises an unmanned aerial vehicle, a data acquisition module and a controller. The data acquisition module is carried on the unmanned aerial vehicle and comprises an ultrasonic sensor array, an infrared thermal imager and an image acquisition module; the controller is used for performing time-frequency domain analysis on the reflected wave to obtain the signal intensity of the reflected wave; the controller performs temperature gradient calculation on the structural adhesive surface temperature distribution image to obtain temperature anomaly region features, obtains optical image textures according to the surface optical image, and outputs an inspection result according to the reflected wave signal intensity, the temperature anomaly region features and the optical image textures; generating an unmanned aerial vehicle flight path according to the three-dimensional model and the curvature parameter of the hyperbolic glass curtain wall, generating obstacle avoidance position information according to environment information set by the hyperbolic glass curtain wall, and updating the unmanned aerial vehicle flight path according to the obstacle avoidance position information; and controlling the unmanned aerial vehicle to automatically inspect the hyperbolic glass curtain wall according to the flight path of the unmanned aerial vehicle.

The invention belongs to the technical field of laser radars, and particularly relates to a Rayleigh wind measurement laser radar frequency discrimination method and system. The frequency discrimination method comprises the following steps: emitting dual-frequency laser to the atmosphere in a time-sharing manner, and receiving an atmosphere echo signal after interaction between the dual-frequency laser and atmospheric molecules; introducing the atmospheric echo signal into an energy detection channel and a Fabry-Perot interferometer channel through a spectroscope; acquiring the signal intensity of the dual-frequency laser passing through the energy detection channel and the signal intensity of the dual-frequency laser passing through a Brillouin-Perot interferometer channel; and the Doppler frequency shift amount is obtained through the signal intensity of the dual-frequency laser after passing through the energy detector channel and the Fabry-Perot interferometer channel. The method has the advantages of being high in implementation performance, capable of reducing cost and complexity and high in optical stability.

The invention relates to the technical field of sound equipment, and discloses a light follow-up sound equipment based on data analysis and a control system thereof, and the system comprises an audio signal processing module which is used for carrying out the noise filtering of audio data, and extracting the real-time audio signal intensity; the volume regulation and control module is connected with the audio signal processing module and used for regulating and controlling the volume according to the intensity of the real-time audio signal after noise filtering; the frequency analysis module is used for analyzing frequency characteristics of the audio data so as to determine corresponding light color parameters; according to the system, the audio is processed by adopting dynamic filtering and weighting algorithms, and the signal intensity is accurately extracted to regulate and control the volume. High synchronization of light and music is realized through delay compensation and adaptive threshold analysis frequency characteristics in combination with multi-stage dimming, and meanwhile, environment interference correction and system self-inspection are realized, so that the audio-visual experience of a user is improved.

The invention relates to the technical field of optical elements, in particular to an optical filter applied to a medical communication sapphire window. The optical filter comprises a substrate, a main film system, a secondary film system and a metal film system, the main film system is located on one side of the substrate, the secondary film system is located on the other side, opposite to the main film system, of the substrate, the metal film system is located on the upper side of the main film system, the secondary film system is located on the other side, opposite to the main film system, of the substrate, and the metal film system is located on the lower side of the main film system. The main film system comprises four high-refractive-index film layers and four low-refractive-index film layers which are sequentially and alternately overlapped from the substrate to the outside according to the structure of the main film system, and the secondary film system comprises four high-refractive-index film layers and four low-refractive-index film layers which are sequentially and alternately overlapped from the substrate to the outside according to the structure of the secondary film system. The metal film system comprises three layers of Ti, Ni and Au metal film layers which are sequentially and alternately overlapped from the main film system to the outside according to the structure of the metal film system, and the optical filter can realize high transmittance and uniform signal intensity within the wavelength range of a communication channel of 1200-1700 nm, so that high communication efficiency is realized.

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 relates to the technical field of radar data processing, and discloses a scene matching guidance system based on a miniature synthetic aperture radar, which comprises a multi-dimensional acquisition module and an intelligent matching module. According to the system, SAR image data of all target areas and SAR image data provided by echo signals in real time are acquired through a multi-dimensional acquisition module and are classified to form a data set, the multi-dimensional acquisition module performs standardization processing and analysis on the data set to generate a digital elevation model, an intelligent matching module analyzes the authenticity of SAR images of each target area, and the authenticity of the SAR images of each target area is analyzed. The method comprises the following steps: generating a corresponding credible index, setting a monitoring period with a fixed time length, analyzing a fluctuation index of real-time signal intensity and a matching index of an SAR image, quantifying data quality and matching potential, dynamically monitoring high image precision, setting a fluctuation threshold value by an intelligent matching module, judging whether the SAR image has a delay problem or not, and judging whether the SAR image has a delay problem or not. And scene matching guidance and track synchronization are carried out according to the credibility index, the matching index and the digital elevation model, and the scene matching guidance is high in applicability.

The invention relates to a Raman nondestructive testing system for cultural heritage based on a cooling device. Comprising a vacuum chamber, and the vacuum chamber is used for placing a sample and receiving Raman scattering signals generated by the light inlet module penetrating through the vacuum chamber, irradiating the surface of the cultural relic sample and exciting the sample; the cooling device module is connected with the vacuum chamber and is used for efficiently cooling the vacuum chamber and preventing the cultural relic sample from being damaged by a laser heat effect; the control and data processing module is used for monitoring and adjusting the laser power, the chamber pressure and the temperature of the sample table in real time, analyzing the collected Raman spectrum data and outputting a detection result; the laser energy density at the sample can be effectively reduced, and the cultural relic sample is prevented from being damaged due to strong light focusing irradiation; meanwhile, efficient collection of Raman signals in a large light spot range is achieved through the beam expander and the signal collection module, and the problem that the signal strength is weakened is solved.

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.