2038 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 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 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 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 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 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 discloses a signal source tracking-oriented Gaussian process space-time modeling and unmanned aerial vehicle flight planning method, which comprises the following steps of: firstly, acquiring RSSI (Received Signal Strength Indicator) data of a signal source by a sensor carried by an unmanned aerial vehicle, and recording corresponding position information and timestamps to form a space-time data set; based on the data set, space-time modeling of signal intensity is carried out by using a Gaussian process, the future position of a signal source is predicted, and the challenge of the position change of the signal source in a dynamic environment is overcome. And then, in combination with a designed flight planning algorithm, calculating a target position of the unmanned aerial vehicle at the next moment according to a signal intensity distribution prediction result. The flight planning method is divided into an exploration stage and a tracking stage, and the path of the unmanned aerial vehicle is dynamically optimized by adopting an overall variance reduction (IVR) evaluation function and a likelihood weighting (LW) evaluation function respectively. According to the invention, through spatial-temporal distribution modeling of signal intensity and flight path optimization, accurate tracking of the unmanned aerial vehicle on the mobile signal source is realized, and hardware dependence and realization cost are effectively reduced.

The invention discloses a lunar radar horizon tracking method based on a dynamic search center, and solves the problems that an existing method is high in dependence on artificial experience and low in processing efficiency, and the false horizon misjudgment rate is high due to lunar soil non-uniformity interference. Comprising the following steps: performing Hilbert transform on a radar signal to extract an envelope; based on historical horizon data, predicting a dynamic search center of a current channel through Gaussian weighted average and determining a search window; screening local maximum value points in the window as candidate points, and calculating signal intensity, smoothness and edge direction scores of the candidate points; selecting an optimal candidate point as a horizon position through multi-feature linear fusion; and according to the lunar soil interface form and the signal-to-noise ratio dynamic adjustment parameters, tracking and outputting a final horizon path one by one. According to the method, historical path constraints and local signal features are fused, the identification precision and robustness of the lunar soil layered interface in the complex electromagnetic environment are remarkably improved, and the method is suitable for radar data processing of lunar exploration tasks such as Chang'e 4 and the like.

The invention discloses a label-free nano plastic and single cell interaction monitoring imaging method which comprises the following steps: placing a sensing chip attached to cells on an SPRM, and recording a cell SPR image in the interaction process of the cells on the sensing chip and nano plastic; after the cell SPR image and the cell bright field image are compared to determine the corresponding area of the single cell in the SPR image, the deformation data of the cell membrane in the interaction process of the single cell and the nano plastic are obtained according to the SPR signal intensity of the area of the single cell, and the monitoring of the interaction of the nano plastic and the single cell under the resolution of the single cell is realized. The technical support is provided for researching the binding kinetics and cytotoxicity of the nano plastic.

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 discloses a laser radar multi-channel echo data online processing system, which sequentially comprises a data distribution layer, a data processing layer and a data processing layer, the data distribution layer divides the echo data and then sends the echo data to the data cache layer to extract a local maximum value, a filtered sampling point sub-sequence corresponding to the local maximum value and a serial number of the local maximum value in the corresponding filtered sampling point sub-sequence; and inputting the data to be pre-fitted into a data processing layer for pre-fitting and fitting based on a polarization normal waveform fitting function in sequence to obtain the optimized signal intensity and the optimized waveform center position, thereby further obtaining the channel calculation distance of the target. The invention further discloses a laser radar multichannel echo data on-line processing method. The on-line processing system is used for obtaining the spatial position information, the corrected spectral information and the spectral reflectivity of a target. According to the invention, by adopting an FPGA pipeline processing architecture, efficient online processing of multi-channel echo data of the hyperspectral laser radar is realized.

The invention relates to the technical field of wheel spoke plate detection, in particular to a bullet train wheel spoke plate crack online detection device based on phased array ultrasound, which comprises a base, a rotating shaft is rotatably arranged at the center of the upper end of the base, a fixing frame is connected to the upper end of the base, an outer cover is slidably arranged in the fixing frame, an ultrasonic probe is slidably arranged in the outer cover, and the ultrasonic probe is connected with the rotating shaft. And the upper end of the outer cover is connected with a plurality of groups of conveying pipes A. When the outer cover descends, the wheel hub during detection is heated, so that after the wheel hub is heated, the size of a material is increased due to thermal expansion, if a radial plate has cracks, the tip or the surface of the cracks can be expanded more obviously due to expansion, a reflection interface is clearer when ultrasonic waves enter the cracks, and the detection accuracy is improved. The intensity of reflected echo signals is enhanced, a detection system can conveniently recognize tiny cracks, meanwhile, impurities such as condensate water and oil dirt on the surface of the hub can be reduced through heating, the viscosity of a surface coupling agent is reduced, the coupling effect of the probe and the hub is improved, and noise signals caused by poor coupling are reduced.

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 discloses a radio map sensing method and device based on adaptive sampling, and the method comprises the steps: obtaining radio map data of a target region, carrying out the Gaussian fitting of the radio map data, and obtaining a radio map model; sampling operation is carried out in a preset unmanned aerial vehicle control space to obtain a sampling control sequence, and a sampling path is obtained based on the sampling control sequence and a preset unmanned aerial vehicle state transition model; predicting each sampling point in each sampling path through a radio map model to obtain signal intensity and variance; on the basis of the signal intensity and the variance, constructing a reward function by using a confidence boundary architecture on a Gaussian process; constructing an optimization objective function based on a radio map model, a preset unmanned aerial vehicle state transition model and the reward function; and solving the optimization objective function to obtain an optimal control sequence of the unmanned aerial vehicle, and generating an optimal sampling path based on the optimal control sequence. And the map precision and the sampling robustness can be 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 discloses a signal countering intelligent monitoring system of an unmanned aerial vehicle, which relates to the technical field of signal countering and comprises a multi-source acquisition module, a dynamic verification module, a decision analysis module, an intelligent communication module, an integrated radar unit, a spectrum analysis unit, an infrared sensing unit and a sound wave detection unit. Multi-source data fusion is realized through the data association evaluation value, the signal countering effect of the unmanned aerial vehicle is improved through the threat evaluation value R, the hierarchical threat response and the precise matching countering strategy, and when the radar signal intensity normalization value S1 conflicts with the infrared feature matching degree S3, the verification value is calculated according to the voiceprint matching degree S4 and the spectrum matching degree S2, so that the reliability of the unmanned aerial vehicle is improved. Or a standby unmanned aerial vehicle signal recognition system is started for synchronous detection, multi-source data contradiction is solved, the misjudgment rate is reduced, satellite, 5G and Mesh network dynamic switching is achieved, the communication performance of the system is guaranteed through a priority strategy, and the data transmission delay rate is reduced.