1206 results about "Acousto-optics" patented technology

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

The invention relates to the technical field of nondestructive testing, in particular to a leak detection and partial discharge digital imaging detection method and system based on acousto-optic fusion, and the method comprises the following steps: based on channel microphone array sound wave data in a partial discharge signal suspicious region, extracting a sound wave abnormal section, positioning a sound source, matching image edge features, and synchronously marking; and analyzing the phase change of the multi-frequency signal to judge a sound source concentration area, tracking the moving trend of a disturbance point, and outputting an acousto-optic fusion positioning trend track. According to the method, the partial discharge feature recognition sensitivity is improved through high-frequency peak paragraph screening and dominant frequency recognition, the abnormal region positioning precision is enhanced in combination with image edge extraction and sound source space matching, and acousto-optic synchronous positioning and trend trajectory display are achieved through multi-frequency signal phase analysis and image frame disturbance tracking. Through fusion of frequency domain feature extraction, image recognition, dynamic comparison and other actions, the spatial precision of abnormal source recognition and the multi-source fusion analysis efficiency are improved, and the partial discharge traceability and dynamic monitoring capability are enhanced.

The invention relates to the technical field of unmanned aerial vehicle detection and recognition, in particular to an unmanned aerial vehicle detection system and method based on vision, laser radar and sound waves, and the system comprises a sensor unit, a data processing fusion unit and a target recognition tracking unit. The data processing fusion unit performs multi-source data alignment and weighted fusion to extract texture, shape and color features of the image, point cloud generates a depth map, sound wave signals are mapped into a two-dimensional feature map, and weights are dynamically distributed based on sensor reliability to generate a unified feature map; the target identification and tracking unit identifies the type of the unmanned aerial vehicle by using the optimized deep learning model and realizes accurate prediction and updating of position and speed states in combination with Kalman filtering, and the decision response unit triggers sound-light alarm and wireless alarm for the non-cooperative unmanned aerial vehicle in real time and transmits target dynamic information to the ground station. And the target detection accuracy of the unmanned aerial vehicle in a complex environment is improved.

The invention discloses a transformer substation equipment defect real-time identification and early warning system based on an image fusion technology. The transformer substation equipment defect real-time identification and early warning system comprises a data acquisition module used for deploying mobile acquisition equipment, an infrared sensor and a visible light sensor to acquire an infrared image and a visible light image of transformer substation equipment; the data fusion module is used for acquiring a fusion image of the infrared image and the visible light image of the substation equipment by using a scene-equipment decoupling fusion algorithm; the defect identification module is used for identifying equipment defects by using a target detection model according to the fused image and outputting a result; and the early warning module is used for starting acousto-optic early warning according to the defect type of the equipment when judging that the output result is greater than a risk threshold value, and sending an early warning signal to the operation and maintenance terminal and the operation and maintenance platform. Based on the multi-modal image, the accuracy of identifying the equipment defect of the transformer substation is improved, and then the safety production of the transformer substation is ensured.

The invention discloses an ultrasonic enhanced tactile sensor system, a sensor and a sensing method. The tactile sensor system comprises a multi-mode sensing unit and a processing unit. The multi-mode sensing unit integrates an ultrasonic module and a visual tactile sensing module, ultrasonic acoustic impedance matching and optical imaging transmission are achieved through an acousto-optic matching structure, and ultrasonic echo signals and tactile deformation images can be synchronously collected. In the processing unit, an event triggering module detects a contact event based on a tactile image and generates a switching signal, and a self-adaptive processing module dynamically controls an ultrasonic mode, distance measurement during non-contact, and switching to object internal imaging or material property identification during contact according to the switching signal. And the three-level fusion processing module outputs a multi-modal sensing result through signal-level synchronous acquisition, feature-level cross-modal fusion and decision-level task switching. According to the system, multi-dimensional perception of proximity sense, surface texture and deep information is realized, and the pre-judgment and accurate operation capability of the robot in a complex scene is improved.

The invention provides a tunnel event and warning lamp acousto-optic linkage strategy generation system based on AI decision, and relates to the technical field of intelligent traffic, and the method comprises the steps: collecting tunnel traffic event data, vehicle structured data, vehicle coordinates, vehicle flow, vehicle speed, and brightness data inside and outside a tunnel in real time, so as to obtain multi-source heterogeneous data; according to the multi-source heterogeneous data, taking the data matching degree, the space-time consistency and the event confidence as multi-objective optimization dimensions, constructing a weighted objective function, generating a Pareto optimal solution set through a multi-objective optimization algorithm, screening the solution set based on space-time constraint conditions, and removing conflict hypotheses; and determining the final event type and the structured event description of the three-dimensional geographic coordinates. The problems of large illumination energy consumption and poor system linkage in existing tunnel safety management are solved.

The invention belongs to the related technical field of lasers, and provides a high-power subnanosecond-nanosecond laser in order to solve the problems that the range adjustment and the application range of an existing laser are limited, and the structural stability needs to be improved. A modulation semiconductor seed source, an optical fiber pre-amplifier, a light beam isolation system, a high repetition frequency solid pre-amplifier, an acousto-optic modulator frequency reduction module and a multi-stage solid single-pass main amplifier are sequentially arranged along an optical path, continuous adjustable output of repetition frequency and pulse width is achieved, the adjustable range of the repetition frequency is 100 kHz to 1 MHz, the adjustable range of the pulse width is 100 ps to 10 ns, and the adjustable range of the pulse width is 100 ps to 10 ns. The laser power and the light beam quality are remarkably improved, and the method is suitable for the fields of high-precision micromachining, nonlinear optical research, medical cosmetology and the like.

The invention relates to an intelligent sleep adjusting method and system based on closed-loop acousto-optic brain wave entrainment, electroencephalogram (EEG) signals are collected and preprocessed in real time through a wireless dry electrode, and high-precision sleep staging is achieved through a deep learning model. The system adopts a fuzzy PID (Proportion Integration Differentiation) controller to dynamically adjust acousto-optic synergistic stimulation: an acoustic module generates binaural beat signals, an optical module outputs blue light (470nm) and amber light (590nm) pulses, and the brain wave entrainment efficiency is enhanced through phase synchronization (the phase difference is less than or equal to 10 degrees) and golden section frequency coupling (fL is equal to 1.618 fA). Parameters are updated every 30 seconds through closed-loop feedback, the sound pressure level (30-50 dB) and the light intensity (10-100 lux) are adjusted according to the Weber-Fechner law, and the response delay is lt; the time is 200 ms. A three-level safety mechanism monitors gamma wave abnormity, epilepsy sample discharge and impedance overrun in real time, and triggers graded protection (alarming, cutting off light stimulation and shutdown). Clinical verifications show that the entrainment success rates of the delta wave and the theta wave respectively reach 71% and 68%, the sleep improvement effect is good, and a safe and efficient intervention scheme is provided for sleep disorders.

The invention relates to the technical field of defect diagnosis, in particular to a production defect diagnosis method and system for a quartz crystal resonator. The method comprises the following steps: extracting a micro-acoustic response signal of each processing stage based on an ultrasonic excitation and response monitoring device, and carrying out acoustic time-frequency structure analysis and response track trend analysis and extraction to obtain a multi-stage crystal voiceprint behavior track sequence; deploying a multi-angle structured light interferometer array to carry out acoustic monitoring and synchronous visual acquisition, carrying out light stripe form response deviation calculation, and extracting a light stripe form response deviation section; and sound-light behavior frequency response analysis is carried out on the multi-stage crystal voiceprint behavior track sequence and the light texture form response deviation section, acousto-optic mismatch index fitting is carried out, and an acousto-optic fusion feature deviation database is constructed. Through accurate and efficient defect diagnosis and positioning, the production yield of the quartz crystal resonator is improved, and waste and energy consumption of a production line are reduced.

The invention relates to a super-resolution fluorescence lifetime microscopic imaging method and system based on pixel relocation. The method comprises the following steps: S1, carrying out multi-focus parallel scanning on a sample by using an acousto-optic deflector; s2, synchronously collecting a fluorescence intensity image and fluorescence lifetime data through an area array detector and a point detector; and S3, carrying out super-resolution reconstruction on the fluorescence intensity image based on a pixel relocation algorithm, and mapping fluorescence lifetime data to a reconstructed image to generate a super-resolution fluorescence lifetime microscopic image. According to the invention, an AOD is adopted to replace a scanning galvanometer in a traditional TCSPC-FLIM imaging system as a light beam scanner; addressing scanning of AOD, image acquisition of EMCCD and life data acquisition of PMT and TCSPC cards are closely linked by combining well-designed multiple paths of synchronizing signals, and fluorescence life data are distributed to each dot matrix through a later data processing method, so that organic combination of super-resolution and FLIM can be realized without complicated equipment, and SR-FLIM images of samples are obtained.

The invention discloses a defect-free neutral atom array preparation method and system based on dynamic optical tweezers rearrangement, and belongs to the technical field of quantum computing. The invention discloses a defect-free neutral atom array preparation method and system based on dynamic optical tweezers rearrangement. A static optical tweezers array is generated through a spatial light modulator to capture initial atoms, an optimal rearrangement path is planned by adopting a Hungary algorithm, and dynamic optical tweezers are generated through an acousto-optic deflector to implement atom grabbing, moving and releasing operation. According to the method, a weighted Gerchberg-Saxton algorithm is innovatively combined with real-time image feedback, so that the precise rearrangement of the atom array is realized. Important experimental technical support is provided for quantum calculation and simulation, and the application progress of the neutral atom array in the fields of quantum error correction, fault-tolerant quantum calculation, quantum simulation and the like is effectively promoted.

The invention discloses a patrol detection system of an intelligent substation circuit device, and relates to the field of patrol detection of the intelligent substation circuit device, the patrol detection system comprises a patrol detection frame, the patrol detection frame comprises a detection unit, a patrol unit and an analysis unit, the detection unit is used for carrying out defect identification and voiceprint detection on an intelligent substation circuit, and the patrol unit is used for carrying out patrol detection; the detection unit comprises a voiceprint detection module and a voiceprint positioning module. The voiceprint detection module is used for obtaining voiceprint signals of the intelligent substation and the circuit in real time. Through the arrangement mode that the voiceprint detection module, the acousto-optic fusion module and the analysis unit are matched with one another and the voiceprint detection technology, the problems that abnormal voiceprint features of potential faults cannot be found in time when transformer substation equipment is manually inspected and heard are solved, meanwhile, fusion of multiple physical signals such as voiceprint, vibration and an electromagnetic field is facilitated, and the safety of transformer substation equipment is improved. And a cross-modal correlation model is constructed in combination with the graph neural network, so that compound faults can be distinguished accurately.

The invention belongs to the technical field of stator slot wedge detection, and discloses a generator stator slot wedge online detection method and system based on acousto-optic monitoring fusion. The method comprises the following steps: acquiring laser ranging data, acoustic monitoring data and generator working condition parameter data of online looseness detection of a generator stator slot wedge; preprocessing the laser ranging data, the acoustic monitoring data and the generator working condition parameter data to obtain laser ranging features, acoustic features and working condition parameters; and inputting the optical ranging features, the acoustic features and the working condition parameters into a pre-trained auto-encoder for anomaly detection, and obtaining an online looseness detection result of the generator stator slot wedge. By fusing the optical ranging technology, the optical fiber acoustic monitoring technology and the unsupervised deep learning algorithm, the important technical breakthrough in the field of generator stator slot wedge looseness detection is realized, and online stator slot wedge looseness detection can be carried out.

The invention discloses an ultra-high-speed imaging device based on acousto-optic filtering modulation. The ultra-high-speed imaging device comprises a spectrum modulation system, a spectrum imaging system and a data processing system. The spectrum modulation system utilizes an acousto-optic tunable filter (AOTF) to dynamically modulate broadband continuous spectrum light, narrow-band illumination light which rapidly changes along with time is generated, and time information of a dynamic scene is effectively mapped to a spectrum dimension. And the spectral imaging system images the spectral coded dynamic scene to the hyperspectral camera to realize acquisition of spectral space-time information. The data processing system performs spectral crosstalk correction, channel separation and demosaicing reconstruction on the acquired original mosaic image, and recovers a time sequence image according to a spectrum-time mapping relation, thereby realizing single-shot superspeed imaging in a dynamic process. The device has the advantages of being simple and compact in structure, flexible in time window, high in imaging fidelity and the like, and has wide application prospects in the fields of rapid dynamics such as microfluidics, laser processing and ultrafast physics.

The invention discloses an alveolar bone noninvasive detection method based on a spatial offset Raman spectrum technology. The method comprises the following steps: S1, selecting a first near-infrared excitation wavelength and a second near-infrared excitation wavelength to form a multi-wavelength tunable excitation light beam; s2, synchronously acquiring a first group of original Raman spectrum signals under a plurality of spatial offset distances; s3, acquiring a second group of original Raman spectrum signals by using an acousto-optic composite modulation Raman enhancement mechanism; s4, inputting the soft tissue optical parameter set into a joint inversion equation; s5, obtaining a deep alveolar bone Raman characteristic spectrum data set; s6, training an alveolar bone tissue health recognition model; and S7, based on the alveolar bone tissue health recognition model, performing health state judgment on the deep alveolar bone Raman characteristic spectrum data set acquired in real time, and generating an alveolar bone health assessment result. The early screening and dynamic monitoring capabilities of alveolar bone diseases are greatly improved, and the clinical working efficiency of doctors and the doctor-seeing experience of patients are remarkably optimized.

The invention provides a power transmission line external damage risk identification method fusing image and sound features, and belongs to the technical field of power supply. Image frames collected by a camera are processed based on a target detection algorithm, when external damage machinery is identified, a target bounding box is output, and the timestamp of the current image frame is recorded; the microphone array is triggered to carry out audio acquisition, and an acoustic reference signal pointing to the external breaking mechanical direction is generated; visual features and Mel frequency cepstrum coefficient MFCC features are extracted, and acousto-optic time delay is calculated; and determining the vertical distance from the external breaking machine to the power transmission line based on the sound velocity, the acousto-optic time delay and the installation parameters of the camera, and carrying out early warning according to the vertical distance and the voltage grade of the power transmission line. Therefore, through a collaborative fusion mechanism of visual sense and acoustic perception, the problems of high false alarm rate, poor positioning precision and large response delay in external damage monitoring of the power transmission line in the prior art are effectively solved, and the monitoring accuracy and practicability are improved.

Disclosed herein is an optical frequency comb generator for a distributed acoustic anomaly detection system. The system can include a continuous wave frequency modulated laser source configured to generate a laser signal. The system can include an acousto-optical modulator configured to modulate the laser signal by altering an amplitude and / or frequency of the laser signal based on an RF drive signal applied to the AOM, and to output an optical pulse with multiple frequency sidebands based on the modulation. The output can form an optical frequency comb usable detecting and locating acoustic anomalies within a structure under observation.

The invention relates to an acousto-optic coupled intelligent sleep aiding method and system. The method comprises the following steps: constructing an initial sound scene environment and controlling sound and light output to smoothly transit to a reference value; collecting a user respiration signal to obtain a respiration rhythm; adjusting the sound and light output rhythm to be synchronous with the respiratory rhythm; coupling the acousto-optic output with the respiratory rhythm on the basis of keeping synchronization; executing acousto-optic guidance according to the selected sleep aiding mode and the acousto-optic coupling mode, and guiding the respiratory rhythm to a target frequency by adjusting an acousto-optic output change frequency; and when the user is in the sleep state, controlling the sound-light output to smoothly transit to a closed state. By adopting the method, dynamic synchronization and self-adaptive guidance of acousto-optic output and the breathing rhythm of the user can be realized, the problem of rhythm mismatch caused by fixed output rhythm of traditional sleep-aiding equipment is effectively solved, and the sleep-aiding effect is improved.

The invention discloses a current transformer oil level monitoring system based on ultrasonic echo detection, which relates to the technical field of electric power monitoring and comprises the following steps: acquiring original echo time sequence data; calculating the distance between the transmitting end and the top of the metal expander by combining the propagation velocity of the ultrasonic waves in the air; and when the oil level height value is lower than a set threshold value, an alarm signal is triggered. According to the invention, the problems of easy clamping stagnation, complex installation, large temperature drift and environmental interference and the like of the traditional float-type, pressure-type and window observation methods are effectively overcome, remote uploading and local acousto-optic prompt are supported, and intelligent inspection and fault pre-warning identification under unattended operation are realized; and the operation safety, the monitoring reliability and the operation and maintenance intelligent level of the oil-immersed current transformer are remarkably improved.

The invention discloses acousto-optic chalcogenide glass with a high laser damage threshold, the chemical composition formula of the acousto-optic chalcogenide glass is GexSySez, x, y and z respectively represent the mole fractions of Ge, S and Se, x = 10-30, y = 5-40, z = 40-70, x + y + z = 100, and the microscopic network structure of the acousto-optic chalcogenide glass contains a [GeSe4] tetrahedron, a [GeSSe3] tetrahedron, a [GeS2Se2] tetrahedron, a [GeS3Se] tetrahedron, a [GeS4] tetrahedron and a Se ring. The acousto-optic chalcogenide glass provided by the invention has a relatively high laser damage threshold Fth (9.72-15.58 J / cm < 2 > at1550 / 20ns / 5kHz), a relatively low thermo-optic coefficient dn / dT and good acousto-optic characteristics and mechanical properties, is high in near-infrared band transmittance, and has a relatively high laser damage threshold while ensuring a high acousto-optic quality factor. The material can be used as a material basis for developing high-performance and high-stability infrared acousto-optic modulation devices.

The invention discloses a high-power picosecond pulse train laser with programmable sub-pulse energy and a method, and relates to the related technical field of lasers, the high-power picosecond pulse train laser comprises a mode-locked fiber laser, an acousto-optic modulator and a solid amplification chain which are sequentially arranged along an optical transmission path; the mode-locked fiber laser generates a mode-locked picosecond pulse sequence; the acousto-optic modulator performs pulse selection and pulse string grouping on the mode-locked picosecond pulse sequence, and performs pre-programming shaping on sub-pulse energy in a pulse string according to set intensity distribution to generate a pre-shaped pulse string; the solid amplification chain comprises at least one stage of solid amplifier, and the solid amplifier comprises a dichroscope, a laser gain crystal, a coupling optical assembly and an LD pumping source; and the dichroscope is used for focusing the pre-shaped pulse string amplified at the previous stage and the LD pump light transmitted by the coupling optical assembly into the laser gain crystal. Independent programmable regulation and control of the energy of each sub-pulse in the pulse string are realized, and the energy distribution of each sub-pulse in the pulse string can be flexibly adjusted.

The application discloses a kind of acoustic-optical fusion's cold spring methane detection method, system, device and storage medium, comprising: obtaining first preprocessed acoustic measurement data and second preprocessed optical measurement data, obtains environmental measurement data;According to the acoustic measurement data, the optical measurement data and the environmental measurement data, form joint data;According to the joint data extraction joint feature, according to the joint feature determines current methane total concentration, according to the joint data determines current methane total leakage flux.The embodiment of the application can improve the accuracy of cold spring methane detection, and can be widely applied in gas detection technical field.

The invention discloses an acousto-optic radar wind measurement data correction system based on adaptive noise suppression, and relates to the technical field of data correction. Environmental parameters and acousto-optic radar system parameters are combined through a dynamic adjustment module to dynamically adjust a signal-to-noise ratio threshold; the echo signal quality analysis module inputs the frequency spectrum characteristic data and the dynamically adjusted signal-to-noise ratio threshold value into an echo quality model and judges whether the current echo signal is valid or not, if yes, interpolation is carried out by adopting a spatial smooth interpolation method, if yes, the dominant frequency of the echo signal is extracted, Doppler frequency shift is calculated, and according to the detection angle and the laying direction, the Doppler frequency shift is calculated; and calculating a radial wind speed, inverting a three-dimensional wind speed vector and carrying out physical consistency correction. According to the correction system, the dynamic adjustment module is introduced, real-time environment parameters and system operation parameters are combined, and a signal-to-noise ratio threshold value required by judgment is dynamically adjusted, so that a judgment basis can be intelligently self-adapted along with a measurement environment, and the accuracy and robustness of echo signal quality judgment are remarkably improved.

The invention provides an acousto-optic fusion guiding system and method for AUV underwater dynamic docking, and belongs to the technical field of autonomous underwater robot docking, and a first inertial navigation system and a second inertial navigation system are respectively used for measuring absolute positions, postures and speeds of an AUV and a docking station; the USBL array, the USBL beacon, the multi-beam foresight imaging sonar and the camera are used for measuring the measurement information of the AUV in different guiding stages; and the combined filtering module is used for carrying out filtering fusion by adopting a federated Kalman filter and a maneuvering observer based on the relative motion state at the initial moment and the actual measurement information of the AUV acquired by the USBL array, the multi-beam forward-looking imaging sonar and the camera in real time, so as to acquire the global state estimation information of the AUV. Compared with a traditional estimation method, the method is higher in motion state estimation precision, better in robustness and more suitable for underwater dynamic docking.

The invention discloses an acousto-optic combined detection and fusion positioning method and device for underground gas leakage, and belongs to the technical field of industrial safety monitoring. In order to solve the problems of high false alarm rate, insufficient positioning precision, poor dynamic environment adaptability and the like of a single sensor in the prior art, the invention provides a multi-modal signal space-time collaborative fusion technical scheme which specifically comprises an acousto-optic heterogeneous sensor, an integrated MEMS ultrasonic array and a tunable laser spectrum module. Microsecond-level synchronous acquisition of acousto-optic signals is realized through a GPS taming clock, and a cross-correlation time delay compensation model is designed to eliminate space-time mismatch errors. And designing a three-stage dynamic fusion framework: improving LMS adaptive filtering to suppress industrial noise, establishing a light intensity attenuation model in combination with dust environment concentration, carrying out multi-modal feature extraction of acousto-optic signals, carrying out signal preliminary fusion, and judging a gas leakage condition. And constructing an acousto-optic Bayesian joint probability model, and calculating the leakage posterior probability. And optimizing positioning parameters based on a double-Kalman filter group, predicting sound wave time delay by forward filtering, and correcting a light diffusion coefficient by backward filtering to realize three-dimensional coordinate solution. Temperature, humidity and dust concentration parameters are fused in real time, a sound velocity calculation model and a light intensity attenuation factor are corrected, and the robustness of complex working conditions is improved. According to the invention, the advantages of acousto-optic signals are combined, errors of various complex environmental factors are further fused and compensated, the overall error is greatly reduced, and the method has the characteristic of dynamic adaptation, and is very suitable for gas leakage detection and positioning in complex environments such as underground environments and the like.

The invention provides a multi-mode underwater biological intrusion detection method and device, and the method comprises the steps: carrying out the sampling of each sampling grid of a target water area through acoustic equipment and image equipment, and obtaining the acoustic data and image data of each sampling grid; extracting and fusing the acoustic data and the image data of each sampling grid to obtain multi-modal features of each sampling grid, taking the multi-modal features as input of a discriminator in the generative adversarial network, and obtaining a discrimination result output by the discriminator as existence of invasive organisms or absence of the invasive organisms in the sampling grids; under the condition that the invasive organism exists in the sampling grid, sampling and detecting the eDNA environment sample on the sampling grid, and determining whether the invasive organism exists in the sampling grid or not based on a detection result. According to the method, rapid identification is carried out by utilizing multi-modal information and acousto-optic characteristics, the identification accuracy is improved by utilizing eDNA, the defects of a single method are overcome, and the efficiency of monitoring invasive species is improved.

The invention discloses a deep sea mineral lifting unmanned transportation system. According to the system, an unmanned carrier-intelligent execution-elastic scheduling framework is constructed, and the system comprises four modules including unmanned carrying equipment, a communication network system, a scheduling control center and a support safeguard system. The unmanned carrying equipment realizes mineral transportation based on buoyancy driving; the communication network adopts a layered redundant architecture of underwater sound OFDM and a laser emergency link, and high-reliability communication and centimeter-level positioning are guaranteed; the scheduling control center improves the operation efficiency through intelligent task allocation and trajectory planning; the support and guarantee system integrates energy management, digital twin monitoring and emergency response mechanisms. The operation process adopts a mode of mainly unmanned autonomous and assisted by remote monitoring, and the links of ballast diving, acousto-optic docking, buoyancy regulation and control, mother ship dynamic unloading and the like are covered. The deep-sea mineral lifting efficiency, maneuverability and reliability are remarkably improved, and core technical support is provided for deep-sea resource development.

The invention discloses a sleep aiding method and system based on brain wave data, and the method comprises the steps: synchronously collecting brain waves, electrocardiosignals, environmental noise and user voice data through a flexible electrode array, constructing a multi-mode causal graph, and dynamically recognizing the type of a noise source (electromagnetic interference or psychological noise); the method comprises the following steps of: generating a target antagonistic intervention signal (such as reverse sound wave counteracting electromagnetic noise and binaural rhythm relieving psychological pressure) according to the target antagonistic intervention signal, generating dynamically adaptive light pulse and tactile vibration parameters in combination with a psychological-physiological collaborative model, and synchronously outputting sound, light and tactile intervention signals through a multi-modal actuator. Through causal reasoning and multi-sensory cooperative regulation and control technologies, accurate inhibition of noise interference and personalized induction of the sleep state are realized, the sleep time is remarkably shortened, the deep sleep duration is prolonged, and the method is particularly suitable for complex noise environments and anxiety-related insomnia scenes.

The invention relates to the technical field of intelligent security and protection, and discloses an intelligent face recognition and early warning system for monitoring, which comprises a data acquisition module, a feature processing engine, a decision center module and an early warning execution terminal, and is characterized in that visible light and infrared thermal imaging bimodal face data are acquired through a multispectral imaging unit; stable extraction of biological characteristics in an extreme environment is realized; a target path is pre-judged by fusing the real-time track and a historical behavior mode through a long short-term memory network; the decision center dynamically triggers a three-level early warning protocol according to the abnormal level, and links the acousto-optic equipment, the access control system and the mobile terminal to execute blocking operation; and deploying an edge computing node and a cloud collaborative architecture to realize model increment optimization, and adaptively correcting an early warning threshold according to the personnel density gradient by using a dynamic weight adjuster. The problems that a traditional system fails in recognition in a shielding environment, lacks behavior pre-judgment ability and is rigid in early warning mechanism are solved.

The invention relates to a miniaturized medium-long wave infrared solid-state laser in which a thulium-doped laser directly pumps a ZGP crystal, the thulium-doped laser takes two laser diodes with the central emission wavelength of 793 nm as pumping sources, two Tm: YAP crystals with the same parameters are cascaded and placed in a U-shaped resonant cavity to serve as laser gain media, and an acousto-optic Q crystal controls intra-cavity loss in the resonant cavity, so that the thulium-doped laser directly pumps the ZGP crystal. Pulse laser with the wavelength of 1.94 m is output; the 1.94 m pulse thulium laser serves as pump light and passes through the ZGP-OPO module, and 2.8 m signal light and 6.2 m idler frequency light are obtained. The Tm laser outputs 1.94 m laser through primary oscillation to directly serve as a pump source, the ZGP-OPO outputs medium-long wave infrared laser in a nonlinear mode, the overall light path structure of the medium-long wave laser is simplified, and the electro-optical conversion efficiency is improved.