1807 results about "Sound field" patented technology

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 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 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 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 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 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.

The invention relates to the technical field of laser deposition control, in particular to an unmanned aerial vehicle metal part ultrasonic field auxiliary laser deposition system which comprises the following modules: a data acquisition module for acquiring a molten pool thermal field signal, a sound field signal and a laser scattering signal, and performing sampling, filtering and synchronous processing to obtain molten pool original data; the micro-flow digital twinning module is used for establishing a molten pool micro-flow digital twinning model according to the molten pool original data and simulating molten pool micro-flow behavior to obtain micro-flow prediction data; and the microflow ultrasonic regulation and control module is used for generating an ultrasonic pulse sequence according to the microflow prediction data and applying the ultrasonic pulse sequence to the molten pool to regulate and control the flow field. According to the invention, through the molten pool microflow digital twinning module and the microflow ultrasonic regulation and control module, real-time modeling and regulation and control of the molten pool microflow structure in the complex geometric part deposition process are realized, the problem that local vortexes, shear layer differences and flow field anomalies cannot be identified in real time in the traditional technology is solved, and the molten pool microflow evolution can be actively reconstructed.

The invention relates to the field of aviation voice signal processing, and discloses a voice recognition compensation pilot earphone hearing protection method and system, and the method comprises the following steps: collecting multi-modal data, and separating a sound source through tensor decomposition; inferring a pilot state by using a dynamic network; performing context recognition and semantic evaluation on the attention target voice; and finally, dynamically modulating the sound field based on deep reinforcement learning, enhancing the voice in a personalized manner, and outputting after noise suppression. The system comprises a multi-mode perception data acquisition module, a sound source decoupling module, a pilot state inference module, a voice processing and semantic evaluation module and a sound field modulation and output module. According to the invention, high-fidelity speech extraction is realized through multi-modal perception and tensor decomposition; evaluating priority key information in combination with attention and semantics; and deep reinforcement learning and model prediction control are adopted to dynamically optimize the sound field, so that the voice recognition accuracy and the pilot information acquisition efficiency are improved.

The invention provides an acoustic coalescence elimination method for hydrogen bubbles in molten aluminum, and belongs to the technical field of molten aluminum bubble elimination. According to the method, sound field collaborative focusing is achieved by arranging a phase control array transducer set in a molten aluminum smelting furnace, primary gathered sound waves and efficient coalescence sound waves are applied in stages according to bubble size evolution in a double-frequency scanning mode, and the hydrogen bubbles in the molten aluminum are eliminated. A target frequency is dynamically adjusted in combination with a bubble resonance frequency optimization model to match the inherent frequency of a bubble, a sound-bubble coupling dynamic tracking system is used for monitoring bubble evolution triggering stage switching in real time, and a sound field focus point dynamically scans and covers a three-dimensional space area through phase delay control. A delay detection method is adopted to eliminate cavitation bubble interference and accurately measure the hydrogen content, sound intensity and frequency parameters are optimized according to a sound field parameter self-adaptive regulation and control model, and the technical problem that hydrogen bubbles in a molten aluminum deep area are difficult to be effectively driven by sound waves and cannot be fully coalesced and eliminated is solved.

The invention relates to the technical field of environmental noise monitoring, and discloses a road traffic noise intelligent monitoring and three-dimensional sound field reconstruction system, which comprises an acoustic sensor module, a data collection and storage module, a data analysis and evaluation module, a three-dimensional sound field construction and display module and a traffic flow feature library. According to the system, a differential geometry principle is adopted, a sound field is regarded as a Riemannian manifold with a local microstructure, and accurate description of an irregular sound field is realized through a curvature self-adaptive sound field manifold construction technology; introducing a covariant derivative in Riemannian geometry, and constructing a sound propagation model adapted to a complex road environment; and realizing hierarchical decomposition and reconstruction of the sound field by using a multi-scale analysis theory. According to the method, the sound source positioning precision and the calculation efficiency are improved, seamless analysis from microcosmic to macroscopic is realized, an innovative solution is provided for traffic and noise collaborative management, and intelligent traffic and environmental noise management are effectively supported.

The invention relates to the technical field of robot control, and discloses a robot peripheral control method and system based on machine learning. The system comprises an environment perception module, a dynamic decision-making module and an execution optimization module, wherein the environment perception module is used for acquiring real-time multi-modal data, including visual image sequences, depth information, temperature gradient distribution and sound field spectrum characteristics, of an external environment and inputting the real-time multi-modal data into a machine learning model; the dynamic decision module processes data through a multi-task joint trained neural network model, and outputs a preliminary control strategy containing a peripheral type identifier, an action sequence template and an initial parameter set; and the execution optimization module combines the current attitude dynamics constraint and the energy distribution state of the robot, corrects the preliminary strategy, generates an executable control instruction, and sends the executable control instruction to the target peripheral. The system adapts to control requirements in a complex environment through multi-link cooperation, and is suitable for various robot application scenes.

The invention provides a physical model driven deep neural network sound field reconstruction method under a small sample condition. The method comprises the steps of obtaining a training sample; establishing a deep learning neural network, wherein the input and output of the neural network are spatial position coordinates and sound pressure values corresponding to the coordinate positions respectively; training a neural network model by using the training sample; and performing sound field reconstruction on the target area by using the trained neural network model. According to the invention, the physical law of sound wave propagation is introduced into the training process of the neural network, so that the neural network not only can learn the characteristics of data in the training process, but also can follow the physical characteristics of sound wave propagation, thereby realizing sound field reconstruction with higher precision.

The invention discloses a method for realizing ocean sound field prediction based on a pre-training optimized physical information neural network, which comprises the following steps of: pre-training: constructing a hypothetical ocean environment, generating simulation data in a sound pressure envelope form by using an acoustic numerical calculation tool, and pre-training the physical information neural network to learn a physical rule of sound field propagation; fine tuning: adjusting an energy scale factor according to the proportion of the sound pressure amplitude of the actual measurement point to the sound pressure amplitude of the pre-trained environment, and performing fine tuning by using the envelope amplitude data of the actual measurement sound field for the pre-trained physical information neural network to obtain an ocean sound field prediction model through a pre-training-fine tuning dual-stage strategy; and ocean sound field prediction: according to the ocean sound field prediction model, obtaining a target position envelope from the to-be-predicted range, and then converting the target position envelope into a sound pressure result to realize ocean sound field prediction. The method can improve the high-frequency sound field modeling precision and training efficiency, and can be widely applied to the fields of ocean sound field modeling, sound source localization and environment inversion.

The invention discloses a spatial projection regularization method for sound source localization and sound field reconstruction and a related device, and belongs to the technical field of sound source localization. Specifically, according to the method, an equivalent source method model is utilized, and an external radiation sound field of a sound source to be measured is simulated through a series of virtual sources. Then, according to the first sound pressure transfer matrix from the virtual source arrangement surface to the holographic measuring point plane and the sound pressure of the holographic measuring point, a space projection regularization algorithm is used for solving the inverse problem, and therefore the equivalent source intensity is obtained; and then, reconstructing an external radiation sound field of the sound source to be detected by using the second sound pressure transfer matrix and the equivalent source intensity. And finally, by taking the maximum sound pressure amplitude as a standard, screening field points in an external radiation sound field so as to determine the position of the sound source to be detected. According to the space projection regularization algorithm, truncation processing of the vector space is carried out with the projection size of the measurement information in the vector space as the criterion, real information is reserved, and noise interference is restrained to the maximum extent.

The invention belongs to the technical field of industrial automation control, and particularly relates to a control system and method of a battery shell cleaning machine, and the method comprises the steps: obtaining a sound field signal in a cleaning tank, and carrying out the preprocessing to remove direct current drift and low-frequency mechanical vibration; the permutation entropy of the sound field signals is calculated to evaluate load complexity, a penalty factor of variational mode decomposition is adaptively constructed according to the load complexity, and then a fundamental frequency mode and a high frequency mode are separated; constructing a risk index reflecting the cavitation erosion degree according to the energy ratio of the high-frequency mode and the time domain volatility of the high-frequency mode; and according to the deviation between the risk index and the safety threshold, cooperatively adjusting the frequency jitter amplitude and the power amplitude of the ultrasonic generator. According to the method, through a self-adaptive decoupling damage signal and double-variable cooperative control strategy, on the premise that high cleaning efficiency is guaranteed, destructive cavitation and resonance damage are effectively restrained, and the balance between the cleaning effect and workpiece safety is achieved.

The invention belongs to the technical field of acoustics, and particularly relates to an index type open-pore rigid plate internal vector sound field calculation method, program and equipment and a storage medium. According to a Webster equation satisfied by a simple harmonic plane sound source excitation sound pressure field, circular piston radiation acoustic impedance on an infinite baffle plate is adopted to represent radiation impedance at an opening of an exponential open pore, a sound field analytical solution of any depth in the open pore of the exponential open pore rigid plate is constructed, system calculation is carried out in combination with sound source conditions, and a sound field of any depth in the open pore of the exponential open pore rigid plate is obtained. Therefore, sound field quantities such as internal accurate sound pressure and vibration velocity of the exponential type open-pore rigid plate under the vertical incidence condition can be quickly solved, and sound field distribution conditions under different section change rules and different open-pore rigid plate sizes can be calculated. According to the method, the calculation complexity is low, the influence problem caused by sound field changes under the non-free field condition can be solved, and the calculation stability and reliability under the complex boundary condition are ensured.

The invention discloses a bridge expansion joint acoustic monitoring method based on a beam forming microphone array, and the method comprises the steps: synchronously collecting acoustic signals through multiple channels, and achieving the high-precision signal alignment through clock offset compensation; the noise analysis module is started by combining a pre-triggering signal of a vehicle passing through the detection unit, the optimal microphone distance is dynamically determined according to sound field coherence and a signal-to-noise ratio maximization model, and a stepping motor drives a movable microphone to achieve real-time adjustment. On the basis, a spatial filtering weight is generated by adopting a self-adaptive beam forming algorithm, and directional enhancement and interference suppression of the expansion joint sound source are realized. Through collaborative optimization of a hardware structure and a signal processing method, the sensitivity and accuracy of acoustic monitoring of the bridge expansion joint are effectively improved, the abnormal sound source recognition capability can be remarkably enhanced, the environmental noise interference is reduced, and the method is suitable for intelligent monitoring and diagnosis of the long-term service state of the bridge expansion joint.

The invention discloses a novel induction-type magneto-thermo-acoustic detection method for the conductivity of a supercapacitor, and relates to the technical field of nondestructive material detection.The method comprises the steps that a steady-state static magnetic field and a pulse alternating magnetic field are introduced to form a composite excitation field, and a magneto-acoustic effect and a thermo-acoustic effect are simultaneously and cooperatively excited in a solid-state electrode material; the magnetoacoustic-thermoacoustic coupling effect is formed, eddy current induced by a pulse alternating magnetic field in the material not only generates joule heat, but also generates a direct carrier of Lorentz force under the action of a steady-state static magnetic field, the two physical effects are derived from the same electromagnetic excitation process, but the mechanisms for generating acoustic signals are complementary to each other, so that the effect of the magnetoacoustic-thermoacoustic coupling is achieved. The two effects are coupled as a unified sound source item, a sound pressure wave equation is established, the equation describes a sound field excitation process under the combined action of a force source and a heat source, the coupling mechanism remarkably enhances the strength and information abundance of ultrasonic signals, and the inherent defect that a single thermoacoustic detection method is insensitive to a high-conductivity material is overcome.

The invention provides a marine acoustic environment monitoring system based on a noise map. The marine acoustic environment monitoring system comprises a buoy network module, a data fusion processing module, a noise map generation module, a noise source identification module and an edge response module, the buoy network module serves as a sensing tail end, multi-source information is gathered to the data fusion processing module through the first data bus for standardization processing, and then the noise map generation module is driven through the second data bus to construct a three-dimensional sound field model. The output of the model is transmitted to a noise source identification module through a third data bus for intelligent analysis and traceability; the alarm decision of the noise source identification module is output to the edge response module, and the edge response module dynamically regulates and controls the communication and acquisition strategy of each buoy node through a distributed control circuit to form a complete closed loop. According to the invention, high-precision and automatic monitoring of the marine acoustic environment is realized, the problems of limited monitoring range and single data dimension of the traditional means are solved, and the reliability and emergency capability of the system are improved.

The invention relates to the technical field of machine vision detection, and discloses a sealing ring vision detection system and equipment thereof, and the sealing ring vision detection system comprises a non-contact suspension and rotation driving module, a full-surface synchronous imaging and reconstruction module, a self-adaptive attitude control module based on image feedback, a defect analysis and directional reinspection module and a comprehensive evaluation and sorting control module. A sound field is generated through the non-contact suspension and rotation driving module, and the sealing ring is suspended in a detection area in a non-contact manner and is driven to stably rotate; when the sealing ring rotates, the full-surface synchronous imaging and reconstruction module synchronously acquires image data of the upper, lower, inner and outer side walls of the sealing ring; and the self-adaptive attitude control module based on image feedback corrects the suspension attitude of the sealing ring in real time. The system identifies and confirms defects by combining high-speed dynamic initial inspection and static directional reinspection strategies, and solves the problems of detection blind areas, positioning errors and complex structure caused by mechanical contact and multi-station transfer in the prior art.

The invention discloses a sound barrier sound insulation characteristic evaluation method suitable for a real ship complex sound field, and belongs to the technical field of real ship sound barriers, and the method comprises the steps: arranging hydrophone arrays at acoustic mirror symmetry positions at two sides of a real ship fairing sound barrier to form an in-situ measurement pair; controlling the ship to sail at a plurality of navigational speeds, and synchronously acquiring sound pressure time domain signals on two sides; carrying out preprocessing and time-frequency analysis on the signals, and calculating sound pressure levels of a sound facing surface and a sound backing surface to obtain an in-situ sound pressure level difference; and based on the sound pressure level difference at different navigational speeds, analyzing the change rule of the sound insulation performance along with the frequency and the navigational speed, and carrying out comprehensive evaluation. In addition, by arranging a vibration sensor and a turbulence measuring device, path separation of structural sound and flow-induced noise is achieved, spatial coherence weighted average is introduced, and the accuracy and representativeness of evaluation under a complex sound field are improved. The method overcomes the limitations of laboratory test environment distortion and single working condition, and can truly and comprehensively reflect the actual sound insulation efficiency of the sound baffle in the dynamic navigation of a real ship.

The invention discloses a conference sound reinforcement system based on an AI intelligent algorithm and 360-degree omni-directional noise reduction, and relates to the technical field of audio signal processing, the conference sound reinforcement system comprises a conference management center, the conference management center is in communication connection with the following modules: a multi-sound-source sensing module used for capturing 360-degree omni-directional sound field information in a conference environment and constructing a sound source space distribution model; according to the invention, the omnidirectional microphone array unit covers all directions of a conference space, synchronously collects audio data streams, eliminates the limitation of a conventional unidirectional microphone, combines the sound source positioning space mapping unit, constructs a sound source space distribution model based on the time difference of arrival and the phase difference through a deep learning model, and improves the sound source positioning accuracy. The azimuth angle, pitch angle and distance parameters of the sound source are accurately analyzed, the position of the sound source is mapped to a virtual space coordinate system, a dynamically updated 3D sound source distribution diagram is generated, the position change and intensity distribution of the sound source are reflected in real time, and the positioning precision in a complex acoustic environment is remarkably improved.

The invention discloses a low-frequency sound propagation loss forecasting method suitable for a polar region sea area, and the method comprises the steps: building a two-dimensional ice layer model of a forecast sea area according to remote sensing data based on the setting that sea ice of the polar region sea area is a uniform elastic medium; calculating hydrological conditions of the ocean sound channel of the polar sea area; establishing a forecast sea area two-dimensional seabed model according to the seabed topography sediment database; an under-ice sound field model is constructed based on a three-dimensional cylindrical coordinate system, sound pressure from unit intensity sound sources with different sizes and depths to a receiving point in a forecast sea area is calculated through a frequency domain finite element method in combination with a PML technology, and sound propagation loss of a needed position is obtained through calculation. According to the method, the application limitation of traditional ray and normal wave theories under complex boundary conditions is broken through through a finite element method, a synergistic effect mechanism of actual ice layer parameter space change, submarine topography fluctuation and sound velocity profile gradient characteristics is systematically analyzed, and sound field modeling is more accurately carried out on different ice layers and submarine topographies in the Chukong sea region all year round; the influence of sound wave propagation is simulated.

The invention provides a factory boundary noise online monitoring traceability system and method, and belongs to the technical field of noise monitoring. The system comprises a data acquisition module; the data processing module is used for judging whether factory boundary noise processing is carried out or not; when the boundary noise processing is determined to be carried out, determining a direction corresponding to the directional microphone with the maximum sound level as a noise source direction; based on the noise source direction, a data acquisition instruction is generated and sent to the data acquisition module, and audio frequency information and video information, collected in real time and fed back by the data acquisition module, in the noise source direction are recycled; and taking the audio frequency information and the video information in the noise source direction as input parameters, and based on a pre-established abnormal sound source positioning model and a pre-established sound feature recognition model, obtaining a noise source visual sound field cloud picture and a noise classification recognition result. The purposes of noise comprehensive response, noise orientation definition and noise accurate traceability are achieved, evidence is provided for factory boundary noise source definition, and disputes are effectively avoided.