2468 results about "Sound field" patented technology

The invention relates to the technical field of voice processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a voice intention recognition method, device and equipment and a medium, and the method comprises the steps: obtaining a to-be-processed voice signal, carrying out the voice activity detection processing of the voice signal, dividing the voice signal into a plurality of voice segments, analyzing semantic contents of the plurality of voice segments, determining semantic correlation information of each voice segment, analyzing sound source attributes of the plurality of voice segments, determining sound field type information of each voice segment, screening out a target voice segment from the plurality of voice segments according to the semantic correlation information and the sound field type information, and executing intention recognition processing based on the target voice segment to generate an intention recognition result. According to the invention, through a dual analysis mechanism of semantic correlation information and sound field type information, effective screening of voice segments is realized before voice recognition, non-target voice or interference segments are effectively prevented from being sent to an intention recognition model, and the accuracy of a recognition result is improved.

The invention discloses an electrical equipment operation state monitoring method, system and terminal, full life cycle health management of equipment is realized through multi-dimensional perception and intelligent analysis, a composite sensor network can be constructed from the level of the method, and high-frequency current, ultrahigh frequency, fiber grating temperature vibration, multi-parameter gas and acoustic sensors are integrated. Electromagnetic characteristics, mechanical states, environmental parameters and voiceprint characteristics are covered; the adaptive signal processing technology performs classification and noise reduction on multi-source data, and the three-dimensional digital twin model realizes time-space fusion of a temperature field, a vibration field, an electric field and a sound field; a lightweight space-time convolutional network is deployed to fuse a time domain waveform, a spectrogram and spatial distribution characteristics for diagnosis, and a hidden semi-Markov model and a particle filter algorithm are combined to dynamically predict the residual service life of equipment. The system architecture comprises a self-organizing sensor network with edge computing capability, a time-sensitive industrial communication network and a containerized analysis engine, and supports mixed reality visual interaction.

The invention relates to the technical field of AI toys, and provides an AI toy voiceprint recognition interaction method, device and equipment, and the method comprises the steps: obtaining a to-be-recognized target voice signal, extracting an original audio data set to generate a sound field estimation parameter and a background noise feature, carrying out the voiceprint feature extraction of the target voice signal, obtaining a voiceprint feature vector, and obtaining the voiceprint feature vector; and performing feature clustering on the voiceprint feature vector and a preset child voiceprint vector set to obtain user identity information, a behavior tag and an emotion tag so as to generate a corresponding multi-modal response instruction, and inputting the multi-modal response instruction into a control module of the AI toy. Robustness of a target voice signal in a complex environment is improved by combining sound field estimation parameters and background noise features, and through voiceprint feature vector extraction and clustering and similarity calculation, the target voice signal is improved under the condition that environmental noise interference is remarkable or semantic emotion interaction is complex. The problems of low identification accuracy and low user discrimination degree exist in the prior art.

The invention relates to the technical field of new material detection, and particularly discloses an ultrasonic flaw detection method and system for a carbon steel bar. The method comprises the following steps: acquiring an appearance image and a section label, constructing a probe path, generating a sound field compensation factor, collecting and preprocessing an echo signal to form a multi-modal signal sequence, further extracting time sequence and spatial characteristics of the multi-modal signal sequence to generate fusion representation, and finally realizing defect classification and label generation. And dynamically updating model parameters and path configuration based on a classification result. The method can improve the detection intelligence and robustness under a complex structure, has high adaptability, high precision and high self-optimization capability, and is suitable for intelligent defect identification of industrial grade carbon steel materials.

The invention relates to the technical field of noise maps, in particular to a noise map dynamic deduction method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: carrying out the space-time alignment of a multi-cluster low-dimension feature vector in an edge calculation node, and obtaining a multi-cluster low-dimension feature vector; generating a three-dimensional sound field reconstruction parameter of the first target data sequence and a spectrum energy distribution parameter of the second target data sequence; based on the three-dimensional sound field reconstruction parameter and the spectrum energy distribution parameter, dynamically controlling the sensor cluster to sleep and generating a space-time difference parameter; hierarchical encryption is carried out on the time-space difference parameters and the two types of data sequences in the dormancy period, and a basic ciphertext sequence and a feature ciphertext sequence for verification are generated; according to the method, the noise deduction map with space-time continuity is generated, high-precision dynamic deduction and energy efficiency optimization of the noise map are achieved, the evolution rule of noise along with time and space is effectively reflected, the real-time performance and accuracy of noise data are improved, and the actual situation of the noise can be reflected more truly, efficiently and in real time.

The invention provides an immersive concert experience system based on virtual reality, and belongs to the technical field of virtual reality, and the system comprises a dynamic adjustment module which is used for predicting the preference of a user for stage arrangement, light effects and music types through a machine learning model according to the historical preference data of the user, and outputting the preference to the stage arrangement, light effects and music types; dynamically adjusting visual elements and sound field parameters of the virtual scene and a refresh rate and a field angle of the virtual scene in combination with the user physiological indexes and the user head motion trail which are acquired in real time; the action capture and feedback module is used for capturing an interaction instruction sent to the dynamically adjusted virtual scene by the limb action of the user in real time; and the interaction feedback module is used for enabling the virtual performer to respond to the interaction instruction of the user in real time based on the expression recognition and voice synthesis technology, and generating personalized interaction feedback content. A user constructs an immersive music interaction field domain, and experience logic of a virtual music meeting is completely reconstructed.

The invention discloses a high aspect ratio micropore pulse abrupt change current copper filling method and system, and belongs to the technical field of printed circuit board manufacturing, and the method comprises the steps: obtaining micropore structure parameters, and generating a gradient pulse abrupt change current waveform; monitoring a deposition thickness parameter of the orifice of the micropore in real time, and when the deposition thickness parameter exceeds a preset thickness threshold value, activating the reverse peak clipping pulse group; generating a resonant composite sound field in the electroplating bath; detecting the concentration distribution of the additive in the micropores in real time, and generating a dynamic adjusting instruction according to the concentration distribution of the additive; the independent injection rate of the accelerator and the inhibitor is controlled according to the dynamic adjusting instruction; and based on the gradient pulse abrupt change current waveform, the resonant type composite sound field and the dynamic adjusting instruction, the copper filling process is executed till the target deposition parameters are achieved. According to the method, a multi-field coupling mechanism of gradient pulse dynamic peak clipping, composite sound field synergistic mass transfer and additive concentration real-time regulation and control is adopted, and defect-free high-reliability copper filling can be achieved.

The invention is suitable for the technical field of people flow density detection, and provides a scenic spot people flow density detection and early warning method and system, and the method comprises the steps: collecting real-time passenger flow data through an intelligent device disposed at a key node of a scenic spot; preprocessing the collected data and then constructing a multi-dimensional feature analysis model, wherein the multi-dimensional features comprise people flow composition features, behavior pattern features and environment coupling features; constructing a sample set based on feature vectors output by the multi-dimensional feature analysis model, outputting the sample set to a deep learning model to calculate a people flow density index, and triggering graded early warning when the people flow density index exceeds a first preset threshold value; generating multi-language voice early warning information according to the graded early warning, and performing regionalized broadcasting through directional sound field equipment; and when the people flow density index exceeds a second preset threshold value, generating a tourist shunting scheme including optimized path planning, thereby effectively improving the accuracy of people flow density detection and the timeliness of early warning.

The invention provides a visual communication advertisement design system and method, and the method comprises the steps: carrying out the cross-modal feature alignment of a background voiceprint feature extracted from environment voiceprint data of an advertisement putting scene and a frequency domain feature of illumination intensity in illumination intensity data, and obtaining an environment perception state tensor; generating a dynamic illumination matrix by combining the spectral irradiance distribution in the environmental perception state tensor with the anisotropic highlight coefficient of each sub-region in the target advertisement picture; determining an audience space domain according to the space depth data of the advertisement putting scene and the audience motion trail, and performing space audio redirection on the target advertisement based on the audience space domain and the sound field energy distribution in the environment perception state tensor to obtain an acoustic beam width angle; and performing acousto-optic synchronous dynamic rendering on the advertisement content of the target advertisement according to the dynamic illumination matrix and the acoustic beam width angle. By adopting the scheme of the invention, acousto-optic collaborative rendering and acousto-optic parameter dynamic adaptation can be performed on the target advertisement so as to realize directional propagation to audiences.

The invention relates to the technical field of structural design, and discloses a topology and size joint optimization design method and system for a hierarchical composite structure, and the method comprises the following steps: dividing a structural domain into a plurality of hierarchical sub-domains, defining the size constraint range of each sub-domain, and distributing a multi-phase material for each sub-domain; grid discretization processing is carried out on the structural domain, a topological design variable is given to each discrete unit, acoustic unit modeling is carried out on the sound field domain, sound pressure boundary conditions are defined, and coupling boundary conditions are applied to the interface of the sound field domain and the structural domain; solving an acoustic-structure coupling equation based on a finite element method, calculating an objective function and constraint conditions, analyzing the sensitivity of the objective function to topological variables by adopting an adjoint method, and iteratively updating the topological design variables through an optimization algorithm until a convergence criterion is met; and on the basis of a topological optimization result, constructing a neural network agent model of an input layer, a hidden layer and an output layer, and carrying out global optimization on sub-domain size parameters by adopting a genetic algorithm so as to minimize a target function.

The invention provides an oil and gas equipment leakage acoustic characteristic intelligent identification early warning method and system, and relates to the technical field of oil and gas equipment safety monitoring, and the method comprises the steps: arranging a sonic sensor array to collect signals, calculating a wavefront propagation path, optimizing the wavefront curvature, carrying out the multi-scale decomposition of a sonic signal, and extracting time-frequency characteristics; and reconstructing a sound field by using an acoustic propagation function to determine a leakage point space coordinate. The method can accurately identify the acoustic characteristics of oil and gas equipment leakage, improves the leakage point positioning precision, achieves the early warning of leakage, and guarantees the safe operation of oil and gas equipment.

The invention relates to the technical field of sound quality enhancement, in particular to a sound quality improvement method and device of a Bluetooth loudspeaker box, equipment and a storage medium. The method comprises the following steps: collecting sound box environment acoustic signals, and carrying out peripheral audio time-frequency spectrum analysis and three-dimensional sound field fitting to construct a peripheral three-dimensional sound field model; based on the surrounding three-dimensional sound field model, environment noise source semantic deep analysis is carried out, and user real-time scene sound quality demand prediction is carried out, so that real-time scene sound quality demand features are generated; bluetooth sound box loudspeaker monitoring parameters are collected, and adaptive noise frequency suppression adjustment is carried out based on the surrounding three-dimensional sound field model rate, so that a loudspeaker dynamic noise suppression adjustment strategy is generated; and acquiring a Bluetooth audio output signal, and performing band frequency response characteristic optimization according to the real-time scene tone quality demand characteristics to obtain a frequency response tone quality optimized audio signal. According to changes of different environments and requirements, the output tone quality of the Bluetooth loudspeaker box is optimized in real time, and high-fidelity audio output is kept.

The invention provides an intelligent video sound box regulation and control system based on AI. The intelligent video sound box regulation and control system comprises a video data processing module, a user behavior analysis module, an environment perception module, a computing power scheduling module, a parameter optimization module, a real-time interaction module and a data storage module. The video data processing module analyzes the video stream and extracts multi-dimensional features; the user behavior analysis module generates behavior tags by analyzing user actions and voice instructions; the environment sensing module collects environment light intensity, space size and sound field parameters; the computing power scheduling module dynamically allocates GPU and TPU computing power resources; the parameter optimization module generates sound box regulation and control parameters based on the user behavior label and the environment parameters; the real-time interaction module adjusts the volume, the frequency response and the video playing frame rate of the sound box according to the regulation and control parameters; and the data storage module synchronizes video streams and regulation and control parameter historical data through distributed storage nodes. The system operation efficiency and the resource utilization rate can be improved.

The invention discloses a three-dimensional noise mapping method and system based on point cloud, and belongs to the technical field of urban environmental noise prediction.The method comprises the steps that point cloud data driven three-dimensional modeling and parameter extraction are carried out, an urban three-dimensional model with a geometric topological structure is constructed through laser scanning point cloud data, and related parameters are extracted; based on sound field calculation of ISO 9613 standards, a multi-path propagation model including an atmospheric effect, a ground effect and obstacle diffraction is established, a green infrastructure noise reduction effect is especially considered, and propagation attenuation of noise in a three-dimensional space is simulated; and performing visual expression of three-dimensional noise, and constructing fusion expression of a sound pressure level contour surface and a three-dimensional city model. In view of difficulty in simulation of three-dimensional reconstruction and sound waves in a spatial propagation process in the prior art, the method improves the precision of quantitative prediction, and fuses a green infrastructure noise reduction effect to realize rapid and efficient regional three-dimensional reconstruction and noise mapping.

The invention relates to the technical field of safety and environmental protection, in particular to a negative-pressure circulating explosion-control dust removal method suitable for combustible dust places, which comprises the following steps: firstly, sealing a bin body and injecting carbon dioxide-nitrogen inert gas to generate a low-oxygen environment; then, a flow guide angle-adjustable cyclone separator, a dielectric barrier discharge plasma reactor and a waste heat thermo-acoustic transducer are driven to cooperatively capture dust, and sound node amplitude synthesis capture data are obtained through compressed sensing of a microphone; inputting the environment data and the capture data into a reinforcement learning process containing a micro-thermochemistry model, and outputting instructions for adjusting negative pressure pulse, inert flow, sound field intensity and cyclone geometry; in combination with distributed radio frequency imaging data, an adversarial digital twinborn model is generated to predict explosion free energy, and automatic rollback or shutdown is carried out when the explosion free energy exceeds a threshold, so that a safe, efficient and low-energy-consumption closed loop is formed.

The invention provides a self-adaptive collaborative acoustic environment active treatment system and method. The system comprises a multi-dimensional environment sensing network module, an intelligent voiceprint recognition and sound field prediction module, an active noise control module, a central intelligent collaborative regulation, diagnosis and self-learning module and a passive acoustic intervention module. The multi-dimensional environment sensing network module collects multi-dimensional sensing data in real time; the intelligent voiceprint recognition and sound field prediction module outputs a voiceprint recognition result and a noise source space coordinate and predicts a sound field evolution trend; the active noise control module outputs a residual noise signal; the central intelligent cooperative regulation, diagnosis and self-learning module outputs an active and passive cooperative control instruction set; the passive acoustic intervention module controls broadband noise to block or change its propagation path. According to the invention, through a dual-channel self-learning mechanism of the deviation diagnosis capability, continuous evolution of system performance can be realized according to a deviation autonomous optimization acoustic model and a control strategy, and accurate, efficient and prospective active treatment is carried out on a complex noise environment.

The invention discloses a self-adaptive sound effect management method and system with a scene analysis module, and relates to the field of self-adaptive sound effect management, and the method comprises the following steps: S1, collecting environmental acoustic characteristics and user behavior data in real time through the scene analysis module; s2, dynamically extracting user hearing preference parameters and scene classification labels; s3, constructing a virtual audition sweet zone matched with the physical space; and S4, dynamically adjusting the phase delay and the energy distribution proportion of each frequency band, and generating an optimal loudness equalization curve meeting the multi-scene constraint. According to the method, adaptive matching of sound field characteristics is realized in a complex dynamic scene through a multi-level perception-optimization closed-loop architecture, acoustic feature extraction and physical space modeling are deeply fused, the technical boundary of traditional pure signal processing is broken through, and the problem of multi-target conflict is solved based on cross-modal collaborative learning and a global optimization algorithm.

The invention discloses a wireless loudspeaker box group cooperative control method and system based on an external Bluetooth transmitting and receiving array, and relates to the technical field of wireless audio control. UWB high-precision positioning and Bluetooth RSSI fingerprint data are fused, an error correction model is constructed, environmental interference data are acquired in real time in combination with spectrum scanning, and the problems of single-technology positioning drift and signal crosstalk are solved. And adopting an improved K-means clustering algorithm, dynamically and adaptively partitioning the sound field according to the movement speed and density of the user, and optimizing the physical topology path of the Bluetooth array based on the interference intensity. A user density change rate, a cluster offset distance and an interference intensity threshold are set, sound field reconstruction is triggered in real time, and partition lag of a traditional scheme is avoided. The Bluetooth array is controlled to switch narrow beam directional transmission, and a multi-user priority arbitration model is combined, so that the concurrent bearing capacity of the system is improved. A wireless sound box group cooperative control scheme integrating dynamic sound field adaptation, high-concurrency instruction scheduling, anti-interference transmission and cross-brand compatibility is realized.

The invention relates to the technical field of audio processing, in particular to a self-adaptive scene sound effect adjusting method and device and a storage medium, and the method comprises the steps: collecting a mixed audio stream and an original playing audio, and extracting an acoustic fingerprint vector through a pre-trained convolutional neural network; performing acoustic feature deconstruction on the acoustic fingerprint vector to obtain a plurality of acoustic feature components, performing scene recognition judgment according to a preset scene judgment rule based on the plurality of acoustic feature components, and determining an audio playing scene; constructing a time-frequency mask according to the audio playing scene, generating a noise reduction gain matrix based on the time-frequency mask, and performing scene sound field enhancement on the audio playing scene to obtain a sound field optimization matrix; and performing noise reduction and sound effect adjustment on the original playing audio according to the noise reduction gain matrix and the sound field optimization matrix, and outputting the optimized playing audio. According to the invention, sound effect adjustment can be dynamically adapted according to different scenes, and the noise reduction accuracy and the multi-scene sound quality adaptability are improved.

The invention provides a sound field optimization method and device of a multichannel loudspeaker array, equipment and a medium, and relates to the technical field of acoustics, to-be-played audio signals are respectively input to each phase compensation filter for phase compensation filtering, and a plurality of phase-compensated audio signals are obtained; the phase compensation filter is determined according to the phase compensation value of the loudspeaker; respectively inputting each phase-compensated audio signal into a corresponding loudspeaker so as to control the multi-channel loudspeaker array to produce sound; acquiring sound field response data in the target area; and when the difference between the sound field response data and the target sound field data does not meet the set sound effect requirement, dynamically adjusting the phase compensation value of the loudspeaker, and repeating the step of phase compensation filtering until the difference between the obtained sound field response data and the target sound field data meets the set sound effect requirement. According to the invention, through a dynamic adjustment mechanism and a closed-loop optimization process, precise regulation and control of the sound field of the loudspeaker array are realized, and the sound effect quality in the target area is significantly improved.

A fiber optic distributed sensing system and method. The fiber optic distributed sensing system includes: an optical fiber extending through an underwater gas field; an interrogator connected to the optical fiber so that light transmitted through the optical fiber is capable of being sensed by the interrogator; and a computer system configured to obtain sensor data captured by the interrogator and determine an amount or a characteristic of gas within the underwater gas field based on the sensor data. The method includes: capturing sensor data using a fiber optic distributed sensor extending through an acoustic field; performing a wavelet transform on the sensor data in order to obtain spatiotemporal data; and matching the spatiotemporal data to an event template of a predetermined set of event templates in order to identify a spatiotemporal event.

The invention relates to the technical field of sound beam control, and provides a sound beam forming pointing control method based on crowd recognition and related equipment thereof. The method comprises the following steps: performing time-space synchronous acquisition and calibration on multi-modal sensor data to obtain a time-space aligned original data set, and performing layered signal enhancement on the original data set to obtain a visual feature tensor and an audio feature tensor; dense crowd detection and tracking are carried out according to the visual feature tensor to obtain a target crowd space-time trajectory matrix, and sound source localization and beam weight calculation are carried out in combination with the audio feature tensor to obtain a beam forming weight vector; performing multi-constraint dynamic optimization in combination with environmental parameters in the multi-modal sensor data to obtain an adaptive control parameter set, and finally performing real-time beam forming in combination with a loudspeaker sequence to obtain a directional sound field output signal. According to the invention, target detection, sound source localization and dynamic adaptive control are combined on the multi-source data, so that the beam direction is dynamically adjusted.

The invention discloses a GIS equipment defect accurate positioning method and system based on acoustic visualization, and relates to the technical field of defect localization, and the method comprises the steps: collecting a vibration acoustic mixed signal in an equipment operation state, and separating the vibration acoustic mixed signal into a pure acoustic signal and a vibration signal through independent component analysis; an acoustic characteristic spectrum is constructed for the pure acoustic signals, a sound field propagation path model is generated, and meanwhile a corresponding relation graph of equipment components and the acoustic characteristic spectrum is established; and determining a source component and a specific position of the abnormal acoustic characteristic spectrum through an acoustic reverse tracking positioning algorithm in combination with the sound field propagation path model and the corresponding relation map. According to the method, by combining vibration acoustic conjoint analysis and acoustic reverse tracking, high-precision positioning of defects of hidden parts in the GIS equipment is achieved, the positioning precision and the recognition accuracy are improved, recognizable defect types are expanded, and the method is suitable for GIS equipment of different structures.

The invention relates to the technical field of laser particle size analyzers, in particular to a laser particle size analyzer with a double-ultrasonic structure, which comprises a particle size analyzer body, a sample pool is arranged on the particle size analyzer body, a sample dispersion mechanism for crushing particle blocks is arranged in the sample pool, and a stirring auxiliary mechanism for preventing suspended particles from settling is arranged above the sample pool. The stirring auxiliary mechanism can push the particles to a sound field strong area of the sample dispersion mechanism so as to improve the dispersion efficiency, and a splash-proof covering mechanism is arranged at the upper end of the sample pool. By arranging the sample dispersion mechanism and adopting a mode of combining phase orthogonality and material orthogonality layout, a stable three-dimensional acoustic vortex can be formed in the sample pool, and the coverage range of the ultrasonic cavitation effect can be obviously improved, so that the particle dispersion uniformity is improved, and the particle dispersion efficiency is improved. A detachable low-frequency ultrasonic vibrator is adopted at the bottom, so that the penetrating power of a high-concentration and high-viscosity sample is further enhanced, and dispersion dead angles can be effectively eliminated.

The embodiment of the invention relates to the technical field of artificial intelligence, in particular to a security behavior event recognition method and system based on multi-modal analysis, and the method comprises the steps: collecting a multi-modal monitoring data set of a target monitoring scene, the multi-modal monitoring data set comprising a visual imaging data stream and an environment sensing data stream; performing spatial feature extraction processing on the visual imaging data stream to obtain a motion state feature set of the target object; time sequence feature extraction processing is carried out on the environment sensing data stream to obtain an environment state feature set, and the environment state feature set comprises a sound field distribution feature, a temperature gradient feature and an illumination intensity feature; and carrying out space-time fusion processing on the motion state feature set and the environment state feature set to generate a fusion monitoring feature vector, calling an AI security behavior recognition model to carry out event classification processing on the fusion monitoring feature vector, and outputting a security behavior event recognition result of the target monitoring scene.

The embodiment of the invention discloses a noise reduction regulation and control method and device for a self-adaptive sound barrier and a medium, and relates to the technical field of noise reduction, and the method comprises the steps: collecting multi-source vehicle noise data which comprises current sound pressure signal time sequence data, preposed sound pressure signal time sequence data and preposed vehicle point cloud data, according to the front sound pressure signal time sequence data and the front vehicle point cloud data, determining a noise source position prediction result corresponding to a sound barrier front node so as to perform sound field prediction on the sound barrier node, and determining a corresponding sound field energy distribution thermodynamic diagram; according to a preset sensitive frequency band threshold value, a target noise high-frequency band needing to be offset is determined in the sound field energy distribution thermodynamic diagram, so that a reverse sound wave signal corresponding to a phase array offset module is generated, and the target noise high-frequency band is offset; and according to the current sound pressure signal time sequence data and the reinforcement learning strategy, determining dynamic sound absorption regulation and control parameters of the dynamic sound absorption module so as to absorb a low-frequency band.

The invention provides an ultrasonic detection method and system for inverting residual stress by using sound wave phase velocity, and belongs to the field of air coupling ultrasonic guided wave detection. The method is based on an air coupling ultrasonic guided wave sound field propagation finite element model, and guides optimization design of air coupling ultrasonic transducer parameters. The air coupling ultrasonic guided wave detection technology is adopted for conducting non-contact excitation and receiving of guided wave signals on the composite material component with the preset stress through the stretcher. And calculating the phase velocity of the air-coupled ultrasonic guided wave in the composite material component based on a geometric positioning and time difference cooperative gradual difference method. And calibrating the phase velocity in the target composite material and preset stress to obtain a corresponding relational expression, performing phase velocity detection on a composite material component with unknown stress based on a calibration result of the target composite material, and performing inversion to obtain composite material construction residual stress. By adopting the method and the system, the residual stress detection of the composite material component is realized.

The invention discloses an auxiliary decision-making system for cognitive competence assessment of old people, which relates to the technical field of cognitive auxiliary decision-making and comprises an environmental noise acquisition and feature extraction module, a time sequence fluctuation analysis module, a dynamic threshold reconstruction and judgment module, a cross-domain consistency calibration module, a multi-modal synchronous verification module and a dynamic threshold regulation and control module. According to the method, the environmental noise is dynamically analyzed, so that the defects of a fixed noise suppression threshold and a static feature extraction model in the traditional technology are overcome. A sound field energy distribution model is constructed in real time and time sequence fluctuation analysis is combined so that a noise fluctuation interval can be identified, a voice starting point detection threshold value is dynamically adjusted and evaluation precision is enhanced. Through multi-mode synchronous verification combining a reaction time curve and a facial movement track, a time offset error is corrected, a judgment standard is adjusted in real time according to noise changes, misjudgment and virtual high risk early warning are avoided, and therefore the accuracy and reliability of cognitive ability assessment of the old are improved.

The invention relates to the technical field of water treatment equipment, in particular to an ultrasonic water treatment equipment control method and system based on variable-frequency vibration waves. According to the method, based on preset fluid working condition parameters, ultrasonic frequency conversion vibration wave signals covering multiple frequency bands are dynamically generated, and a vibrator array is driven to generate a composite sound field; a cavitation effect and an activation effect are synchronously excited in a fluid medium through variable-frequency vibration wave signals, so that physical form depolymerization and surface charge distribution change of scale forming substances occur; a shearing effect is formed on a fluid-pipe wall boundary layer, an attached state biological membrane structure is stripped, and the microscopic binding force of a crystallized scale body is loosened; monitoring the dispersion degree of scale-forming substances in the fluid and the state of a boundary layer, and adjusting the frequency band combination and energy distribution of variable-frequency vibration waves to maintain scale inhibition; and continuously optimizing the frequency conversion strategy and the sound field intensity according to the feedback data of the scale inhibition maintenance state. Through intelligent multi-band frequency conversion control of the ultrasonic water treatment equipment, efficient and environment-friendly water treatment and scale prevention effects are realized.

The invention belongs to the technical field of geological engineering monitoring and multi-physics field intelligent sensing, and discloses a separation grouting slurry migration monitoring method and system, and the method comprises the steps: constructing an acoustics-optics-electricity-electromagnetism multi-physics field coupling monitoring system; a grouting hole and a monitoring drilling hole array are arranged in a target stratum, a distributed optical fiber sensor, a drilling hole ultrasonic imager, a resistivity measuring device and a transient electromagnetic detection device are installed, and a three-dimensional monitoring network is formed; synchronously acquiring sound field, light field, electric field and magnetic field data; four-field monitoring data and overlying strata multi-parameter observation data are fused, a coal seam mining three-dimensional overlying strata separation model is constructed, and a slurry diffusion three-dimensional visualization model is generated through numerical simulation; and based on the four-field monitoring response difference of the separation space before and after grouting, in combination with a monitoring frequency domain correction model of multiple indexes of grout diffusion, the diffusion range, compactness and filling effect of the grouting grout are evaluated, and abnormal early warning is triggered.