159 results about "Noise energy" patented technology

The invention discloses a drilling multi-source sensing signal denoising method based on dynamic noise decoupling and a self-adaptive mode, and belongs to the technical field of underground processing. The method comprises the following steps of: separating common noise of a noise energy distribution matrix of a sensor and separating specific noise; carrying out adaptive noise set empirical mode decomposition on the separated signals, carrying out variational mode decomposition on residual signals in the signals, and screening effective modes through a kurtosis-entropy joint criterion to obtain signals with effective characteristic components reserved; high-frequency fluctuation of the signal is punished through total variation regularization, an improved alternating direction multiplier method algorithm is used for solving, short-time Fourier transform is carried out on the solved signal, low-frequency and high-frequency features are extracted through a multi-scale convolutional network, and a final denoised signal is output through gating weight fusion. According to the method, the signal denoising precision in a complex noise environment is remarkably improved, the processing time is shortened, and the resource consumption is reduced.

The invention provides a directional pickup method, system and device and a storage medium, and relates to the field of pickup. The method comprises the following steps: performing MVDR beam forming processing on an initial voice signal input by a microphone array, and then extracting a BFCC feature and a fundamental tone frequency feature of the voice signal; and processing the BFCC features by using a pre-trained voice / noise separation DNN to obtain a time-frequency mask. And according to the fundamental tone frequency characteristics, adaptively designing comb filter parameters, and carrying out comb filtering on the initial voice signal. And taking the time-frequency mask as a weighting coefficient, respectively multiplying the weighting coefficient with the voice signal after comb filtering and the initial voice signal, and estimating target voice energy and noise energy. And calculating a Bark gain coefficient related to the frequency on the Bark frequency scale, wherein the Bark gain coefficient is used for enhancing the voice signal in the time-frequency domain. And finally, converting the enhanced voice signal into a time domain signal through inverse BFCC conversion to obtain a target enhanced voice pointing to the target direction. Through the scheme, the directional pickup effect is improved.

The invention discloses a new energy-based centralized area electric power analysis management method and system, and particularly relates to the technical field of photovoltaic power station fault analysis. Direct current side current, voltage and environment air pressure data are collected, an arc noise energy judgment threshold value is dynamically adjusted based on air pressure, and a current change rate difference correction coefficient is generated; a composite index of arc noise frequency band energy and voltage signal abrupt change is constructed, and an arc feature vector is generated in combination with waveform oscillation periodicity; comparing the feature vector with a preset template through a dynamic time warping matching algorithm, calculating a matching weight and a trend slope, and judging an arc reignition event in combination with a dynamic judgment threshold and a continuous increasing condition; and generating a priority breaking instruction sequence based on the event duration, controlling the breaking time sequence of the target string according to the grounding grid impedance distribution, and sending a blocking signal to the inverter in the coverage area.

The invention provides a remote monitoring method and system applied to children's watches, and relates to the technical field of children's watches, time axis synchronous alignment is carried out on collected multi-source heterogeneous data through an interpolation method, data time sequence chaos caused by sampling rate differences is prevented, and then the data time sequence chaos caused by sampling rate differences is prevented. Through dynamic coupling calculation of a light intensity mutation gradient and a heart rate stress coefficient, the cooperative influence of environment change on the physiological state of the child is quantified in real time, and the physiological state of the child is determined by further combining power spectrum centroid frequency and physiological phase difference analysis of the motion rhythm and logarithmic correlation of acoustic envelope frequency and GPS speed. In addition, an acoustic propagation delay compensation mechanism is introduced, a two-factor dynamic equation model is constructed through a time delay cross term, and a dynamic risk threshold generation mechanism based on a noise energy ratio is combined, so that the dynamic risk threshold of the motion intensity, the rhythm characteristics and the acoustic scene is effectively distinguished. Effective remote monitoring on child safety in different scenes is realized.

The invention relates to the technical field of power equipment fault diagnosis, and particularly discloses a pole-mounted circuit breaker mechanical fault diagnosis method and system, and the method comprises the steps: firstly, synchronously collecting a dynamic force-displacement signal, a high-frequency acoustic emission signal and a broadband vibration signal in the switching-on and switching-off process of a circuit breaker operating mechanism; then, the acoustic emission and vibration signals are decoupled into an impact source component and a friction source component which are statistically independent through a blind source separation algorithm; performing envelope spectrum analysis on the impact source component to extract impact characteristics, and performing energy calculation on the friction source component to obtain friction noise energy characteristics; finally, on the basis of dynamic force-displacement curve fitting analysis, in combination with impact characteristics and friction noise energy characteristics, distinguishing and delimiting of mechanical wear and lubrication degradation faults are achieved. According to the invention, the problem that the existing diagnosis technology cannot effectively identify and distinguish the coupling fault of mechanical wear and lubrication deterioration is solved, and early warning and accurate diagnosis of the mechanical fault of the pole-mounted circuit breaker are realized.

The invention relates to the technical field of cooling fan control, and discloses an anti-EMI cooling fan filtering and noise suppression system controlled by a dynamic coupling path, and the system comprises a modeling subsystem which is used for carrying out the electromagnetic energy transfer modeling of a cooling fan, and obtaining an EMI energy balance equation set; the extraction subsystem is used for extracting the electromagnetic interference transfer relation among the components of the cooling fan; the calculation subsystem is used for calculating noise energy distribution data in a preset rotating speed range; the analysis subsystem is used for performing frequency self-correlation analysis on the parameter space distribution data to obtain EMI and noise parameter time sequence characteristic data; the real-time adjusting subsystem is used for inputting the EMI and noise parameter time sequence characteristic data into a prediction model for characteristic operation, PWM control correction parameters are obtained, the output power and the rotating speed of a heat dissipation fan are adjusted, and collaborative optimization among EMI suppression, noise control and heat dissipation performance is achieved through the system.

The invention discloses a distribution network power line anti-interference communication method based on adaptive filtering, and belongs to the technical field of distribution network power line communication. According to the method, a communication signal adopting a frequency shift keying modulation mode is acquired from a power line coupler of a distribution network through a signal acquisition module, the communication signal is preprocessed by using a digital signal processing unit, spectral analysis is performed on the preprocessed signal, and characteristic parameters of interference noise are extracted; a coefficient vector of a finite impulse response adaptive filter is initialized based on the characteristic parameters, the order of the filter is in direct proportion to the reciprocal of the dominant interference frequency, fine adjustment is carried out based on noise energy distribution through a table look-up method or a linear mapping relation, and the weight coefficient of the filter is adjusted in real time in the communication process. The adjustment step length is dynamically adjusted according to the real-time estimated signal-to-noise ratio, and finally, the processed signal is output through the adaptive filter and data demodulation is carried out. The method is mainly used for improving the anti-interference capability and the communication reliability of the power private line communication of the distribution network.

The invention relates to an adaptive noise floor energy detection method and system based on FFT frequency spectrum accumulation, and the method comprises the steps: carrying out the FFT frequency spectrum accumulation of an electromagnetic signal sampled by an ADC in an FPGA, and carrying out the channel division of a broadband frequency spectrum into sub-bands; counting and estimating the top and the bottom of the noise by sub-bands one by one; carrying out median filtering processing, subtraction and modular operation according to the obtained data to obtain optimal values of the energy bottom and the noise energy fluctuation range of each channel, carrying out summation to obtain a noise floor of each sub-band, and carrying out median filtering once to obtain a final noise floor value of each sub-band; and a noise factor is introduced to obtain a final adaptive constant false alarm threshold, and adaptive detection of noise floor energy is realized through the threshold. According to the invention, a parallel operation architecture based on the FPGA is adopted, so that the method is simple in calculation and high in sensitivity, and has the capability of detecting each sub-band signal at the same time.

The invention provides a sparse array tomography SAR three-dimensional reconstruction method and system based on SVD-DCS, and the method comprises the steps: carrying out the preprocessing of complex image registration, phase dechirp processing, and amplitude-phase error correction processing on sparse array SAR image data for solving the problems that the tomography SAR is difficult to reconstruct accurately and there are many false targets under the condition of irregular and sparse sampling; the method comprises the steps of recognizing adjacent equal-height pixels, reducing DCS data processing dimensions through SVD decomposition, and reconstructing a scattering intensity contour of a reference pixel through noise energy estimation and SVD-DCS spectrum estimation; by selecting a model order, estimating a target parameter, carrying out geocoding on data, and outputting a tomography SAR point cloud space position and scattering intensity data, a function of improving density and reliability of sparse array SAR three-dimensional reconstruction is realized. According to the method, the point cloud reconstruction density is high, side lobe noise suppression is better, and the reliability of tomography SAR point cloud reconstruction is improved.

The invention discloses a voice signal processing method and related equipment, so as to ensure that wearable equipment can realize a good pickup signal-to-noise ratio in different noise scenes. The method comprises the steps that a first voice signal collected by a first pickup is acquired, the first voice signal comprises an environment noise signal, and the environment noise signal indicates the environment noise of the environment where the wearable device is located; when a second voice signal collected by a second sound pickup of the wearable device is adopted to execute the voice service, according to the first voice signal, a first time length is obtained, and the first time length is a time length in which the noise energy of the current environmental noise signal is continuously greater than a first energy threshold value; and according to the first duration, determining whether to switch to a third path of voice signal collected by a third pickup of the wearable device to execute the voice service. Wherein when the noise energy of the environmental noise is greater than the first energy threshold value, the signal-to-noise ratio of the third path of voice signal is greater than the signal-to-noise ratio of the second path of voice signal.

The invention provides a voice assistant awakening method, a vehicle-mounted terminal and a storage medium, and relates to the technical field of voice assistants. According to the method, identity information of a user sending suspected wake-up voice data can be recognized, and an initial wake-up threshold value associated with the identity information of the user and historical wake-up habit data of a voice assistant are searched from a preset database; and adjusting the initial wake-up threshold according to the similarity between the real-time wake-up habit data and the historical wake-up habit data and the noise energy to obtain a real-time wake-up threshold. The real-time wake-up threshold is negatively correlated with the similarity and positively correlated with the noise energy, so that the reliability of the obtained real-time wake-up threshold is high, and the suspected wake-up voice data is evaluated to obtain the target wake-up value; and when the target wake-up value is greater than or equal to the real-time wake-up threshold value, waking up the voice assistant. Because the reliability of the real-time wake-up threshold is high, the wake-up of the voice assistant at the moment does not belong to false wake-up, and the sensitivity of wake-up of the voice assistant is also high.

The invention provides a vehicle transmission system gear noise online diagnosis method and system and a computer readable storage medium. The vehicle transmission system gear noise online diagnosis method comprises the steps of obtaining a series order set H and a gear meshing frequency of gears in a transmission system when a vehicle runs at a certain gear; a noise sound pressure signal function SP (t) in the driving process of the vehicle at the gear is obtained, a vehicle rotating speed signal function T (tacho) in time synchronization with the noise sound pressure signal SP (t) is obtained, SP (t), T (tacho), H and the gear meshing frequency are processed, and a power density function Lh (w) of the corresponding gear is obtained; calculating order component energy A according to the power density function Lh (w) of the corresponding gear; calculating critical bandwidth energy B according to the power density function Lh (w) of the corresponding gear; calculating dark noise energy C, wherein C = B-A; calculating a difference value between a gear order component energy conversion component and a dark noise energy conversion component; and judging whether the noise is easily perceived by human ears. According to the invention, the gear with noise problem can be quickly positioned.

The invention provides a fault information detection method and system for an HPLC communication module, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting physical layer dynamic parameters of a power line carrier signal through a main transmission channel and a redundant transmission channel, comprising carrier signal attenuation, noise interference spectrum density, instantaneous bit error rate and channel impedance abnormal identification; 2, performing multi-dimensional fault feature decoupling on the dynamic parameters of the physical layer to generate a quantitative fault feature set; and step 3, based on the quantized fault feature set, dynamically dividing an interference action range according to spatial correlation between signal attenuation gradient distribution and noise energy. According to the method, the complex interference of the power line is accurately identified and specifically processed, and the reliability and the communication quality of the HPLC communication module are effectively improved.

The invention discloses an online modeling and control method for a narrowband active noise control system, which comprises the following steps of: (1) performing frequency estimation on a signal picked up by a reference microphone by using a triangular cascade adaptive notch filter algorithm, and calculating an online estimated value of a signal-to-noise ratio by using energy of an input signal and an output signal of a notch filter; (2) when the online estimated value of the signal-to-noise ratio is larger than a preset value, modeling and control are started, a reference signal and auxiliary noise are generated based on the estimated frequency, and a control signal is calculated; (3) estimating auxiliary secondary sound by using the auxiliary noise; (4) estimating the sum of the primary sound and the secondary sound of the error signal at the noise frequency by using the reference signal; (5) updating the estimation of the frequency response of the secondary path at the auxiliary noise frequency and the frequency response of the auxiliary filter at the narrow-band noise frequency; (6) obtaining the estimation of the frequency response of the secondary path at the narrowband noise frequency in an interpolation mode; (7) updating the filter coefficient of the controller; and (8) outputting a control signal to drive a secondary source loudspeaker to produce sound, propagating the sound through a secondary path, and coherently superposing the sound with the initial noise signal at the error microphone to realize a noise reduction function. According to the method, the secondary path can be accurately modeled online, compared with an existing algorithm, the auxiliary noise energy is low, the convergence speed is high, the noise reduction effect is good, meanwhile, the problem that the same parameter operation results are different in a traditional auxiliary white noise online modeling algorithm is solved, and the algorithm stability is better.

The embodiment of the invention discloses a tunnel construction environment noise suppression method and system applying a deep learning algorithm, and the method comprises the steps: collecting an original noise signal set containing a plurality of time domain noise signals and construction equipment noise components contained in the time domain noise signals, and completely obtaining complex and diversified noise information in a tunnel construction environment; based on noise feature distribution obtained through noise feature extraction processing, noise features can be comprehensively described from multiple dimensions of noise spectrum features, noise source orientation features and noise energy propagation features; performing suppression processing on the features by using a deep learning noise suppression model, and intelligently analyzing and generating a targeted suppression control feature set; furthermore, a noise suppression device is driven to execute noise cancellation operation based on the set, and cancellation sound wave signals opposite to the time domain noise signals in phase can be accurately generated.

The invention relates to the technical field of data reasoning, and discloses a spring fatigue crack initiation early warning method and system based on acoustic emission, and the method comprises the steps: extracting a background noise segment of an original acoustic emission signal flow in a spring fatigue test process; according to noise energy distribution in the background noise segment, a dynamic noise threshold value is generated in a self-adaptive mode; synchronously inputting acoustic emission event signals exceeding a dynamic noise threshold in the original acoustic emission signal flow into a time domain analysis channel and a frequency domain analysis channel; extracting a time domain feature vector of the acoustic emission event signal, and extracting a frequency domain feature vector of the acoustic emission event signal; fusing the time domain feature vector and the frequency domain feature vector to obtain a crack sensitive parameter of spring fatigue; judging a crack initiation probability value of the target spring according to the crack sensitive parameters; when the crack initiation probability value continuously exceeds the fatigue probability threshold value, obtaining a crack initiation early warning instruction of the target spring; the accuracy of spring fatigue prediction can be improved.

The utility model relates to a staggered and superposed wave-shaped sound barrier which comprises a base and a frame. The base is fixedly connected with the frame, and the plate body, the first wave-shaped screen body assembly and the second wave-shaped screen body assembly are sequentially installed on the inner side of the frame from front to back. Wherein the first wave-shaped screen body assembly and the second wave-shaped screen body assembly are similar in structure, each wave-shaped screen body assembly is composed of a plurality of wave-shaped sound absorption strips, and the left side face and the right side face of each wave-shaped sound absorption strip are both wave faces; the wave-shaped sound-absorbing strips in the first wave-shaped screen body assembly and the wave-shaped sound-absorbing strips in the second wave-shaped screen body assembly are arranged in a staggered manner, are overlapped with each other and then are fixedly connected with the plate body; and a wave-shaped sound barrier is formed. According to the wave-shaped sound barrier, the two layers of wave-shaped screen body structures are overlapped in a staggered mode, so that the path of sound waves is more complex when the sound waves pass through the sound barrier, the reflection, diffraction and absorption capacities of the screen bodies on noise are improved, noise energy is effectively weakened, meanwhile, the sound barrier can present rich light and shadow effects and dynamic aesthetic feeling along with changes of light rays and observation angles, and the sound barrier is more attractive. And the appearance is more attractive.

The invention discloses a self-adaptive ultrahigh frequency partial discharge signal extraction device and method based on dual-mode noise reference, and relates to the technical field of communication, and the device comprises a dual-sensor cooperative collection system which comprises a directional ultrahigh frequency sensor group and a noise feature learning module; the self-adaptive noise elimination device is connected with the dual-sensor collaborative acquisition system; and the intelligent signal identification system is connected with the self-adaptive noise elimination device. An auxiliary sensor in the directional ultrahigh frequency sensor group is specially used for collecting environmental background noise, and the noise feature learning module is used for extracting a time-frequency domain feature spectrum of the background noise by using Hilbert-Huang transform, so that the device can know the feature change of the noise in real time. Meanwhile, a dynamic threshold value adjusting unit in the self-adaptive noise elimination device can automatically adjust a signal triggering threshold value according to the noise energy level, automatic tracking of noise changes is achieved, and the adaptability of the device to the complex noise environment is greatly improved.

The embodiment of the utility model discloses a testing device and system for friction noise of a handheld moving coil microphone, and the device comprises a testing main body, the testing main body comprises a testing part and a stabilizing part, and the side surface of the testing main body is transversely provided with a handheld control rod; the testing part comprises a fixed outer ring, and a rubber ring is arranged in the fixed outer ring; the stabilizing part comprises a balancing weight connected to the fixed outer ring through a long bolt, and the balancing weight is arranged on the opposite side of the rubber ring. According to the testing device, the rubber ring is arranged to simulate a human hand, the external part of the handheld moving-coil microphone is directly contacted when the testing device is used, so that the noise generated by friction in the using process of the handheld microphone is simulated, the structure is simple, the noise is convenient to use and collect, and standardized collection can be formed; and multi-dimensional evaluation analysis is carried out on the friction noise from the dimensions of noise energy, spectral characteristics and the like to form comprehensive performance indexes.

The invention provides a cooling fan and electronic equipment, and relates to the technical field of cooling structures. The cooling fan comprises fan blades, a shell and a supporting piece. The shell is provided with a mounting cavity, the fan blades are arranged in the mounting cavity, a plurality of first micro-penetrating holes are formed in the shell, and the first micro-penetrating holes communicate with the mounting cavity. The supporting piece is arranged on the shell. According to the cooling fan, the shell is provided with the multiple first micro-penetrating holes, the supporting piece, the shell and the electronic equipment define the first noise reduction cavity, in this way, a Helmholtz resonance noise reduction structure is formed, noise energy can be dissipated, and the working noise of the fan blades is reduced. Moreover, the first noise reduction cavity is formed by the gap between the shell of the cooling fan and the electronic equipment, so that the noise reduction effect can be ensured while the internal space of the electronic equipment is fully utilized, and the lightness and thinness of the electronic equipment are improved.

This application relates to the field of monitoring data processing technology, and particularly to a method, device, and storage medium for preventing monitoring data from being tampered with. The method includes: during the recording of monitoring data, simultaneously acquiring a thermal noise segment from an imaging sensor for each video frame, reducing equipment costs and deployment difficulty; calculating the image activity metric of the video frame and the noise energy metric of the thermal noise segment, requiring minimal computation and meeting the simple real-time needs of ordinary monitoring equipment; performing an arithmetic combination of the image activity metric and the noise energy metric to obtain a frame verification feature value, which is then associated with and stored with the video frame, making it difficult to forge and having low storage overhead; acquiring the video frame to be verified and generating a verification feature value based on the video frame; determining that the monitoring data has been tampered with when the deviation between the verification feature value and the stored verification feature value exceeds a preset range, thus achieving low-cost, low-complexity, and high-real-time monitoring data integrity protection.

The embodiment of the invention discloses an extended target detection method, belongs to the technical field of radar detection, and solves the problem that the detection performance is reduced due to the fact that excessive noise is introduced or target energy is omitted during energy accumulation in an existing extended target detection method. Comprising the following steps: constructing a dynamic planning accumulation detection model of a distance extension target based on an echo matrix; on the basis of the minimum energy loss criterion, balancing parameters are configured for the value function, a double-probability joint constraint optimization model about the target energy and the noise energy is established, and the balancing parameters are determined by solving the optimization model; updating a value function and a state transition matrix of the joint state variable among the plurality of pulses through recursive operation based on the trade-off parameter; and for the value function obtained after updating is completed, extracting a corresponding energy ridge line, constructing an approximate probability model of the variation amplitude of the energy ridge line, and obtaining a target extension length value by solving an optimal variation threshold of the approximate probability model under a preset false alarm probability.

The present application provides a directional sound pickup method, system, device, and storage medium, relating to the field of sound pickup. The method comprises: performing MVDR beamforming processing on the initial speech signal input by the microphone array, and then extracting the BFCC features and fundamental frequency features of the speech signal. The BFCC features are processed using a pre-trained speech / noise separation DNN to obtain a time-frequency mask. Comb filter parameters are adaptively designed based on the fundamental frequency features, and the initial speech signal is comb filtered. The time-frequency mask is used as a weighting coefficient and multiplied with the comb-filtered speech signal and the initial speech signal, respectively, to estimate the target speech energy and noise energy. The frequency-dependent Bark gain coefficient is calculated on the Bark frequency scale and used to enhance the speech signal in the time-frequency domain. Finally, the enhanced speech signal is converted into a time-domain signal through an inverse BFCC transform to obtain the target enhanced speech pointing in the target direction. The above scheme improves the directional sound pickup effect.

The invention relates to the technical field of breathing machines, in particular to an improved breathing machine air path noise reduction method and device.The improved breathing machine air path noise reduction device comprises a draught fan upper cover, a draught fan upper silica gel pad, draught fan upper sealing silica gel, a draught fan, a draught fan silica gel supporting frame, a draught fan bin body, draught fan lower sealing silica gel, a draught fan bottom cover and an air inlet silencer. The airflow can flow uniformly and orderly, turbulent flow and vortex are reduced, and noise generated by airflow separation and pressure fluctuation is reduced. Air passes through the silencing silica gel block and then enters the S-shaped air channel of the fan bottom cover, the layout utilizes space, the sound wave propagation distance is prolonged, and more noise energy is consumed. A silica gel corrugated pipe is designed at the air outlet, and the damping performance is improved through a triple mechanism. The contact positions of the fan, the fan bin body and the upper cover are isolated through silica gel, radial impact force and vibration are blocked, and operation noise is reduced. The problem that an existing breathing machine depends on noise reduction cotton to reduce noise, and pollution is prone to being generated is solved.

The application discloses a low-noise tire pattern pitch optimization method and device based on image processing and a medium, and the method comprises the following steps: S1, processing initial pattern information and calculating pitch length; S2, extracting groove boundaries and tire mark boundaries of a pattern pitch graph; S3, inputting basic parameters such as pitch and mark; S4, introducing an A-weighting filter for acoustic weighting; S5, calculating an initial noise spectrum; S6, optimizing a spectrum peak value in a harmonic range; S7, iteratively adjusting a pitch ratio and quantity until noise energy meets a threshold value, and outputting an optimal pitch sequence. Through the fusion of image processing technology and acoustic analysis, the pattern pitch design is systematically optimized, tire noise is significantly reduced, design efficiency is improved, and a research and development cycle is shortened.

The invention relates to an air interface calibration method for a network phase error of an analog domain phase shifter, which is applied to an MIMO (Multiple Input Multiple Output) communication system and comprises the following steps of: establishing a channel model H from a signal transmitting end to a signal receiving end; keeping the channel static state unchanged, and enabling a signal receiving end to periodically send a set number of orthogonal pilot signals S; and constructing an observation model Yk of the pilot frequency receiving signal according to the channel model H, performing conjugate transpose and scaling on the observation model Yk by utilizing orthogonality of the pilot frequency signal S to obtain an equivalent observation model, constructing an optimization problem based on the equivalent observation model, and calculating phase shifter phase error estimation which enables the total noise energy of the pilot frequency receiving signal to be minimum. According to the method, air interface phase error calibration under the condition of no channel state information can be realized, the adverse effect of the phase error on a wireless communication system is reduced, the capacity of the wireless communication system is greatly improved, and the method is suitable for various communication scenes.

The present application relates to the field of rail transportation, in particular to a full-closed sound barrier for rail transportation, comprising a first sound barrier and a second sound barrier, a first channel and a second channel are formed on both sides between the first sound barrier and the second sound barrier, and a sound-absorbing assembly is arranged in the first channel and the second channel, the sound-absorbing assembly is provided with a first sound-absorbing module and a second sound-absorbing module, and a flow path for air circulation is formed between the first sound-absorbing module and the second sound-absorbing module, air flows through the flow path formed by the first sound-absorbing module and the second sound-absorbing module, noise energy is effectively reflected, scattered and absorbed during the propagation process, thereby effectively attenuating the sound wave intensity, greatly reducing the noise level, and gradually weakening the sound wave intensity. The present application also relates to a mounting method of the full-closed sound barrier for rail transportation.

The utility model relates to related technical field of bridge engineering especially, and it is a kind of noise reduction bridge expansion joint, including receiving part, clamping groove, U type damping rubber part, connecting section bar, noise reduction layer, end connecting piece and elastic part, two groups are oppositely equipped with receiving part, the clamping groove is opened in receiving part inside, U type damping rubber part is equipped with between the two groups receiving part in cooperation with clamping groove, the connecting section bar is filled in U type damping rubber part both sides, the noise reduction layer is integrally formed with U type damping rubber part upper layer part.The utility model is through the composite structure of upper microperforation layer, honeycomb core layer and lower microperforation layer, and upper and lower microperforation layer carries out reflection and preliminary absorption to high frequency noise by the micro hole of staggered distribution, and the hexagonal hollow structure of honeycomb core layer provides multiple scattering path for noise, substantially consumes low frequency noise energy, realizes multi-band noise attenuation, significantly improves bridge periphery sound environment.

The present invention relates to the field of audio devices, and discloses a system and method for a magnetic charging case of an adaptive noise-canceling headphone, including: when the noise-canceling headphone is in use, motion data and ambient noise are collected in real time, the motion state of the user is judged, the ambient noise energy entropy is calculated, the scene noise level of the user's location is judged, a noise-canceling strategy is selected for the noise-canceling headphone in combination with the user's motion state, the historical usage data of the noise-canceling headphone is analyzed, the expected usage period of the user is predicted, the remaining power required by the noise-canceling headphone is predicted according to the expected usage period, the actual remaining power is compared, and it is judged whether the power is sufficient. If it is not sufficient, a power risk signal is generated, the real-time collection of motion data and ambient noise is suspended, a model is established, the noise-canceling strategy of the noise-canceling headphone during the prediction period is selected through the model, and the ambient noise and motion state are re-detected at the inspection time point to update the prediction model and the preselected noise-canceling strategy, and the charging power is dynamically adjusted when the noise-canceling headphone is charging.

The invention provides a weak signal adaptive enhancement method, which comprises the following steps that: a feature extraction module performs time-frequency transformation on a noisy input signal and extracts features to form a comprehensive feature vector, and the feature extraction module fuses the time-frequency transformation and a lightweight convolutional network; the comprehensive feature vector is input into a potential function generation network, and the potential function generation network dynamically outputs potential function parameters meeting the bistable condition based on a multi-layer perceptron structure in combination with a physical constraint mechanism; and constructing a time-varying potential function according to the potential function parameters, inputting the time-varying potential function as a restoring force item into a differentiable Langevin equation solver, and calculating a system state evolution sequence through a numerical integration method to obtain an enhanced output signal. The limitation of a traditional fixed potential function model can be abandoned, the optimal potential function parameter is dynamically generated according to the real-time characteristic of the input signal through an end-to-end trainable architecture, and adaptive cooperative enhancement of noise energy to the target signal is achieved.