339 results about "Background noise" patented technology

The application belongs to the field of pesticide residue detection, and particularly relates to a method for determining pesticides in water samples. The method comprises the following steps: amino modification is performed on MIL-100(Fe) to obtain an amino-functionalized MIL-100(Fe) material; and the pesticides in the water sample are analyzed and detected by using SALDI-TOF-MS with the amino-functionalized MIL-100(Fe) material as a substrate. The application forms a special MOF material by performing amino functionalization modification on MIL-100(Fe), which can enhance the interaction force between the substrate and the analyte, exhibits good ultraviolet absorption and energy transfer capacity, and thus improves the desorption / ionization efficiency in LDI detection. The method is used to detect pesticide residues, and in the low mass region, lower background noise and higher signal intensity are exhibited, so that the detection of pesticide substances in the small molecule region is greatly broken through, and the detection limit is greatly reduced.

The application provides an anti-noise signal periodicity anomaly monitoring method and system which overcomes correlation false positives, comprising: a collection step: collecting data signals every preset time interval; a processing step: dividing the collected data signals according to a preset rule and performing feature extraction; a conversion step: performing orthogonal conversion on the extracted features to eliminate the correlation between the features; a monitoring step: processing the converted data to form an MO control chart, and monitoring the MO control chart; and if abnormal data appears, reporting. The MO test based on the EnNRC features can maintain high test accuracy under strong background noise and has stronger anti-noise interference ability.

This invention discloses a noise reduction method for electromagnetic measurements of Rydberg atoms. This method constructs a 509nm coupled optical closed-loop circulation system comprising a polarization beam splitter, a half-wave plate, and a high-reflection mirror. This enables multiple reciprocating propagations of the laser within the atomic gas chamber. Utilizing the optical path circulation mechanism, the coupling strength between light and atoms is significantly improved without increasing the laser source power, thus greatly enhancing the excitation efficiency of Rydberg states. Simultaneously, this structure allows the intermediate frequency carrier signal to linearly and coherently superimpose with the number of cycles, while the laser background noise accumulates incoherently only according to a square root law, thereby significantly improving the measurement signal-to-noise ratio. This invention solves the problems of low excitation efficiency and difficulty in eliminating laser background noise in existing single-path optical systems, providing a new solution with high excitation efficiency and high signal-to-noise ratio for high-sensitivity microwave electric field measurements.

The application discloses a three-dimensional near-infrared spectral tomography reconstruction method based on a mask prior, and belongs to the field of medical image processing. The method respectively performs multi-scale convolution coding on NIRST optical signals and MRI volume data to obtain features, then embeds structural information of a mask as a prior condition into a feature fusion module, dynamically adjusts spatial weights in the fusion process of multi-scale structural information and optical functional information, so that the network focuses on potential lesion areas and suppresses background noise, and finally reconstructs the optical parameter distribution of the tissue through a three-dimensional decoding network. The method provided by the application can effectively reduce the ill-posedness in the NIRST reconstruction problem, reduce artifact generation, improve the positioning accuracy of the tumor area and the optical property reconstruction quality, and reconstruct the optical property parameter distribution of the biological tissue.

This invention relates to the field of valve detection technology, and more particularly to a method for detecting internal leakage in valves based on acoustic emission signals. The method includes: acquiring the topology and geometric parameters of the pipeline network to determine the pipeline location characteristics of each valve; based on these characteristics, analyzing the propagation characteristics of acoustic emission signals in the pipe segment where the valve is located for at least two preset frequency bands, and defining the effective monitoring arc segment for each valve in different frequency bands; establishing a dual-modal coverage matrix between the valve and candidate sensor locations, combined with the background noise level; constructing a discrete optimization function based on this matrix to obtain the sensor installation location combination; deploying sensors to collect signals, extracting multi-frequency band time-frequency domain features, and constructing a dual-modal feature vector; combining the feature vector and the coverage matrix to calculate the probability that each valve is a leakage source, and identifying the valve with internal leakage. This invention achieves accurate detection and location of internal leakage in valves by optimizing sensor layout using a dual-modal coverage matrix and fusing multi-frequency band features.

The present application relates to the technical field of remote sensing image processing and artificial intelligence, in particular to a state space model driven remote sensing image change caption generation method, the method comprises the following steps: obtaining image data and word mapping table of remote sensing image intelligent interpretation; extracting double time phase features through a double time sharing branch feature extractor; constructing a joint input sequence of a decoder according to the difference enhanced features, multi-scale visual features and text sequences; taking the constructed joint input sequence as input, calculating word probability distribution by autoregressive calculation based on a pre-trained language model decoder, completing prediction and cyclic iteration according to the word mapping table, and obtaining complete image change description sentences; the present application solves the problem of losing high frequency details in long sequence modeling of state space model through frequency domain modulation, and effectively suppresses background noise interference by using difference perception aggregation, thereby improving the accuracy of remote sensing image difference description generation.

This application discloses a wind tunnel-based noise detection method, apparatus, storage medium, and electronic device. The method includes: when testing a test piece in a wind tunnel, acquiring a measured noise spectrum in the testing environment and obtaining the operating frequency of the wind tunnel's inverter; matching the background noise spectrum corresponding to the operating frequency in a background noise spectrum library based on the operating frequency; aligning and dividing the measured noise spectrum and the background noise spectrum using a frequency band division rule adapted to the inverter's operating frequency to obtain multiple frequency band units; based on the acoustic energy density of the measured noise spectrum and the background noise spectrum within each frequency band unit, extracting the energy component corresponding to the background noise spectrum from the measured noise spectrum through directional orthogonal projection, and reconstructing the spectrum of the residual energy after extraction to obtain the effective aerodynamic noise spectrum of the test piece; and calculating the noise detection result of the test piece based on the effective aerodynamic noise spectrum.

This invention relates to the field of target recognition technology, and in particular to a radar target recognition method and system based on micro-Doppler sensing attention. First, a micro-Doppler time-frequency map is generated based on the radar echo signal. Second, the micro-Doppler time-frequency map is input into a lightweight backbone network for feature extraction to obtain an initial spatiotemporal feature map. Third, a dual attention mechanism is used for the first residual compression feature extraction to obtain a first-stage feature map. Then, the first-stage feature map is input into a max-pooling layer for feature downsampling to obtain a downsampled feature map. Next, a dual attention mechanism is used for the second residual compression feature extraction to obtain a second-stage feature map. Finally, the second-stage feature map is input into a classification output module for classification calculation to obtain the radar target recognition result. This invention achieves high-precision target classification under strong background noise by introducing a time-axis integral pooling mechanism and a channel attention mechanism that conform to the physical laws of incoherent accumulation of radar signals.

The present application belongs to the field of geophysical exploration and geoscience information sensing technology, and relates to an intelligent sensing system for ground construction risk monitoring, comprising: a pulse generation module for generating a detection pulse sequence with a preset time interval; an orthogonal polarization modulation module for mapping the detection pulse sequence with an orthogonal polarization state and loading a time delay modulation; a distributed sensing module for receiving pulse combination and generating a backscattering signal; a common mode interference cancellation module for superimposing the backscattering signal in the photon domain to generate a phase push effect, in-situ canceling a static resident stress background noise, and extracting a dynamic birefringence phase shift amount; and a signal decoupling analysis module for identifying a dynamic shear signal according to a covariance tensor principal eigenvalue extraction value. The present application utilizes an optical domain physical interference cancellation mechanism to annihilate static background interference, realizes high-fidelity physical extraction of weak dynamic signals, and improves the identification ability of the system for structural medium shear instability.

The application provides a cable aging online monitoring method and device based on a spread spectrum time domain reflection method, which comprises the following steps: establishing a frequency-variable distribution parameter model based on the physical structure of a cable, performing background noise spectrum scanning on the cable to identify a spectrum hole, and taking the spectrum hole as a working frequency band of a detection signal; generating a detection signal matched with the working frequency band, and injecting the detection signal into a live cable; collecting echo signals of the cable, performing adaptive signal decomposition on the echo signals to obtain purified echoes, performing cross-correlation operation on the purified echoes and the detection signal, and extracting reflection response features; performing phase dispersion compensation on the reflection response features to obtain dispersion-corrected reflection responses; extracting multi-dimensional feature vectors of the dispersion-corrected reflection responses, inputting the multi-dimensional feature vectors into a physical information neural network, and inversely obtaining insulation aging quantitative indexes and cable aging grades of each position of the cable.

This invention discloses a laser image signal-to-noise ratio (SNR) enhancement method based on single-camera dual-channel imaging, relating to the fields of optical microscopy, digital image processing, and machine learning. The method includes: acquiring the original image from a single camera; separating the original image into a green channel image and a red channel image; constructing a denoising model based on the linear relationship between the green and red channel images, using the minimization of background noise in the green channel image as the objective loss function of the denoising model, and solving for an optimized parameter set; processing the green and red channel images according to the optimized parameter set to obtain a high SNR laser image after removing fluorescence background noise. This invention can remove fluorescence background noise from the original image acquired by a single camera without increasing hardware costs, effectively eliminating spectral crosstalk in the laser channel and significantly improving the laser image signal-to-noise ratio.

This invention provides a target detection method, apparatus, electronic device, and storage medium. The method includes: acquiring echo data received by a vehicle-mounted radar; performing a Fast Fourier Transform (FFT) on the echo data to obtain range-Doppler two-dimensional data; and performing detection processing on the range-Doppler two-dimensional data according to a preset pre-detection tracking model to obtain a target detection result. The preset pre-detection tracking model includes at least a particle filter-based pre-detection tracking model. The preset pre-detection tracking model employs a first preset likelihood ratio function, which includes a background noise amplitude term and a sum term of the target's amplitude and the background noise amplitude. Using this invention can reduce the computational resources consumed by particle filter-based pre-detection tracking algorithms for target detection, thereby reducing its computational cost.

This invention proposes a multi-target detection method based on entangled photons. First, a pump light is generated using a continuous narrow-linewidth semiconductor laser, which, after polarization modulation and focusing, illuminates a PPKTP crystal. A spontaneous parametric down-conversion process generates polarization-entangled photon pairs, which are then separated into signal and reference light. These are received by a single-photon detector to obtain two time series. Second, coincidence measurements are performed on the time series in different scanning directions within the observation area to obtain a coincidence count matrix. Then, a two-dimensional constant false alarm rate (CFAR) detection algorithm is introduced, using ordered statistics to estimate background noise and adaptively adjust the detection threshold to screen candidate target points. Third, a density clustering algorithm based on correlation strength weighting is employed, combining the correlation strength and spatial distribution of entangled photon pairs to detect different targets and suppress isolated noise. Finally, the coincidence count peak points within each target cluster are selected as the final detection targets, thereby achieving multi-target detection with unknown numbers and randomly distributed locations.

The application discloses a kind of underground space optical cable high fidelity sound restoration method based on DAS system, comprising: the real-time signal collected to optical cable is carried out data demodulation, identify whether it contains energy impact signal generated by the optical cable after being padded and being hit, if it contains, the energy abnormal distribution position in energy impact signal is positioned, obtains positioning point;Continuous analysis time domain signal of positioning point, after filtering low-frequency interference signal, phase anomaly signal is rejected;The sound signals of a plurality of equivalent sensing nodes adjacent to the positioning point are superimposed and averaged to suppress additive noise, and then the sound signal is restored.The application can realize rapid positioning according to the spatial distribution mapping relationship of optical cable, and after filtering background noise from the collected signal, the highly correlated signals of multiple spatial sensing nodes near the positioning position are linearly superimposed to suppress additive random noise, and high-fidelity sound signal restoration is realized.

The application discloses an end-to-end audio-visual source separation method based on dynamic gating fusion. The method uses a dynamically adjusted fusion mechanism to effectively fuse audio and visual features through a dynamic gating fusion module, and further separates the mixed audio signal through an audio-visual Transformer decoder. The method can accurately separate the target audio in a complex multi-source environment, significantly improving the quality of audio-visual source separation, especially in the presence of background noise and multiple sources. Experimental results show that the performance of the method on multiple benchmark datasets has been significantly improved, verifying its effectiveness and advantages in the audio-visual source separation task.

This invention relates to the field of acoustic emission signal feature enhancement for aero-engines, and discloses a method, system, medium, and device for denoising weak fault signals under strong background noise in aero-engines. The method includes: acquiring strong background noise signals under normal operating conditions of the aero-engine; performing wavelet packet decomposition and reconstruction to obtain multiple frequency band component signals; constructing a corresponding autoencoder for each frequency band component signal, and using the frequency band component signal as input to perform unsupervised training on the autoencoder; performing wavelet packet decomposition and reconstruction on the acoustic emission signal to be processed to obtain multiple frequency band component signals to be processed; inputting each frequency band component signal to be processed into the corresponding trained autoencoder for reconstruction; calculating the reconstruction error between the input and output signals of each autoencoder; determining whether each frequency band component signal contains outliers based on the reconstruction error; reconstructing the frequency band component signals containing outliers to obtain the denoised fault signal.

This invention relates to a high-efficiency ion current acquisition structure and a mass spectrometer. The ion current acquisition structure includes: a collection chamber adapted to be installed between the ion source and the sampling cone of the mass spectrometer; a trumpet-shaped aperture disposed within the collection chamber at the end facing the ion source; an annular electrode disposed on the inner wall of the trumpet-shaped aperture; and a beam rod assembly comprising multiple rod-shaped electrodes uniformly arranged circumferentially along the outlet of the trumpet-shaped aperture, with adjacent rod-shaped electrodes spaced apart to form gaps; wherein, on the side away from the ion source, the ends of the multiple rod-shaped electrodes are all bent and converged towards the central axis of the collection chamber. This invention provides a high-efficiency ion current acquisition structure that can improve the technical problems of low ion acquisition efficiency before entering the vacuum system and high background noise caused by the inability to effectively filter neutral particles in the prior art.

This invention discloses a method and system for monitoring mechanical damage to batteries during electric vehicle transportation based on acoustic emission spectrum analysis. The method includes: performing multi-scale decomposition of the original signal sequence using wavelet transform to separate high-frequency transient components and low-frequency background noise, obtaining a denoised elastic wave signal; calculating time-domain features, including peak amplitude and duration, based on the denoised elastic wave signal, and combining this with frequency-domain features such as the dominant frequency component to obtain a comprehensive feature vector; if the peak amplitude of the comprehensive feature vector exceeds a preset threshold, it is judged as a potential damage event, and damage-related subsets are extracted from the feature vector to obtain damage candidate features; training the damage candidate features using a support vector machine classifier to obtain damage type labels; and fusing transportation environment data with the damage type labels, using sliding window analysis to track signal change trends and determine the degree of damage evolution. This invention achieves accurate identification, classification, and dynamic monitoring of battery pack transportation damage.

This invention discloses a multi-target adaptive jamming system based on an array antenna, belonging to the field of electromagnetic countermeasures and signal processing technology. The system includes an array antenna unit, a multi-channel RF front-end, a signal processing and control unit, and an environmental sensing unit. The array antenna scans the airspace and captures signals from multiple targets; the signal processing and control unit runs various algorithms to estimate the azimuth, frequency, and power parameters of multiple targets; an interference suppression matrix is ​​constructed based on singular value decomposition, generating multiple low-sidelobe focused jamming beams aimed at each target; the environmental sensing unit monitors background noise intensity in real time and dynamically adjusts the transmission power through a noise adaptive power control algorithm. This invention overcomes the shortcomings of traditional jamming techniques, such as energy dispersion, poor environmental adaptability, and unintelligent resource allocation. It can simultaneously achieve efficient and precise jamming of multiple targets, significantly improving the suppression ratio of a single target, and maintaining high jamming efficiency and resource utilization even in high-noise environments.

The invention relates to a sound system for a vehicle (2), wherein the vehicle (2) has an air conditioning system (4) for its interior, wherein the sound system has an electronic unit (8) and a loudspeaker (6), wherein the air conditioning system (4) is configured to generate a background noise during its operation, wherein the electronic unit (8) is configured to provide at least one specification for an additional noise for the operation of the air conditioning system (4) depending on the background noise and to control the loudspeaker (6), wherein the loudspeaker (6) is configured to output the additional noise.

This invention discloses a system and method for locating corona discharge in generator stator windings. The system includes a track, two symmetrical supports, and a controller. The supports are I-shaped with adjustable support rod height. A movable crossarm slider is mounted on the crossarm rod, with both ends fixed to the crossarm slider. A track slider is fitted onto the track, enabling circumferential rotation and axial stepping movement. A laser mapping and modeling device and a corona discharge detection device are fixed opposite to each other on the track slider. The method includes: system layout; track center calibration; laser mapping and modeling to establish a cylindrical coordinate system; background noise detection; abnormal discharge detection under rated voltage; and data comparison to screen for true discharge points. This invention achieves blind-spot-free detection throughout the entire stator winding. By establishing a dedicated coordinate system through laser mapping and modeling, combined with ultraviolet and acoustic fingerprint detection methods and background noise comparison, it achieves precise coordinate positioning of corona discharge points, adapting to different generator models and automating operation.

The application provides a background noise high-order surface wave dispersion extraction method, and belongs to the technical field of seismology. The method first calculates the cross-correlation function of continuous noise data and performs preprocessing to obtain an original dispersion energy spectrum; then a reference phase shift curve between the energy of the base order and the first high-order mode is extracted; the cross-correlation function is phase-shifted based on the curve, so that the base order and the high-order surface wave are separated in time, the high-order part at the negative time is retained and inverse phase shift is performed, and a cross-correlation function containing only the high-order surface wave is obtained; then the high-order surface wave dispersion energy spectrum is obtained through frequency-Bessel transformation, and is spliced with the base order part in the original spectrum to form an enhanced dispersion energy spectrum; finally, the base order and the high-order dispersion curves are extracted after quality control. The application can effectively suppress the interference of the base order sidelobe on the high-order mode, and significantly improve the continuity and signal-to-noise ratio of the high-order surface wave dispersion energy.

This invention provides an acoustic wave sensing system based on master-slave laser phase-locked loop (PLL). A frequency-locking unit locks the frequency difference between the master and slave lasers to a highly stable reference frequency source, thus separating the acoustic wave signal from the background noise. The slave laser is then exposed to the acoustic field under test, and its output light frequency and phase are modulated accordingly by acoustic wave disturbances. The master and slave lasers generate a heterodyne beat frequency optical signal via a beam combining unit. A phase comparison unit compares this beat frequency electrical signal with a reference radio frequency signal to generate an error signal proportional to the instantaneous phase difference. A servo control unit conditions and amplifies the error signal, driving a tuning unit to adjust the output frequency and phase of the slave laser in real time, forming a negative feedback closed loop. The adaptive compensation characteristics of the closed-loop control give the system a strong ability to suppress slowly varying interferences such as environmental temperature changes and mechanical vibrations.

The application discloses a mud pump accessory fault intelligent prediction method and system, belonging to the technical field of fault diagnosis and prediction. The method comprises the following steps: constructing a multi-dimensional heterogeneous perception array unit to synchronously collect multi-dimensional physical state parameters; performing adaptive time-frequency feature enhancement processing, enhancing weak fault features through variational mode decomposition, envelope spectrum entropy and correlation coefficient double screening, and Hilbert transform; establishing a multi-physical field coupling mechanism mapping, constructing a hydraulics mechanism based on the Bingham model, calculating the pressure residual and flow residual of the measured value and the theoretical value, and fusing the enhanced time-frequency features to construct a physical consistency feature vector; using a long short-term memory network with an integrated attention mechanism to identify the evolution trend; implementing variable working condition migration adaptation and dynamic compensation; and outputting fault diagnosis and life assessment results. Through deep fusion of physical mechanism and data driving, the application effectively suppresses strong background noise interference, and improves the prediction accuracy and generalization ability under variable working conditions.

The application discloses a kind of material aerodynamic acoustic performance online testing method and system, it is related to wind tunnel aerodynamic acoustic performance test field, the application is set in wind tunnel sound-transparent solid wall test section, to be measured acoustic material is installed in its middle part;First, second acoustic sensor is sequentially arranged on the wall surface upstream of material, third, fourth acoustic sensor is sequentially arranged on the wall surface downstream;Respectively collect the sound pressure data of four acoustic sensors under the running state and static state of wind tunnel;Transfer matrix equation set is constructed, and the sound pressure data of running state and static state are substituted into equation set and simultaneously solved, to obtain sound pressure transfer function;According to sound pressure transfer function, the noise reduction of material under current airflow environment is calculated.The application realizes online testing by the synergistic effect of sound-transparent solid wall, four sensor arrangement, double-state acquisition and simultaneous solution of transfer matrix, effectively eliminates wall reflection and wind tunnel background noise interference while testing, and the test result is accurate and reliable.

This application relates to the field of burner combustion control technology and discloses a burner fuel grading control optimization method. This method calculates the background noise energy during a silent monitoring period and selects the frequency of the minimum energy value as the target micro-perturbation frequency. A sinusoidal micro-perturbation signal is generated based on this frequency and superimposed on the command of the shift fuel regulating valve. Valve displacement and combustion chamber sound pressure signals are simultaneously acquired and orthogonal decoding is performed. Electromechanical transfer gain, thermoacoustic gain, and dynamic transmission phase difference are calculated and obtained. Based on the electromechanical transfer gain, it is determined whether amplitude compensation should be performed. A two-dimensional linkage verification matrix is ​​constructed by combining the time derivatives of the thermoacoustic gain and the dynamic transmission phase difference, thereby distinguishing between pure thermoacoustic mode over-limit and physical spatial anomalies, and executing the corresponding fuel grading closed-loop regulation or safety interlocking procedure. This invention eliminates valve mechanical execution errors, accurately distinguishes combustion instability conditions under strong noise backgrounds, and improves the safety of combustion system operation.

A power-transmitter control unit (70) of a power transmitter device (20) calculates an intensity of a power supply request signal based on an output signal of a power-transmitter communication coil (40), and energizes the power transmitter coil (22) when determining that the calculated intensity exceeds a determination threshold. The power transmitter device (20) includes a detection circuit (91) that measures background noise near the power transmitter coil (22). When the measured background noise is large, the power-transmitter control unit (70) sets the determination threshold to a larger value than the determination threshold when the background noise is small. When the measured background noise is large, the power-receiver control unit (230) of the power receiver device (100) sets the intensity of the power supply request signal to be larger than the intensity when the background noise is small.

The application relates to a vehicle sealing performance detection method and device, a vehicle, a storage medium and a product. The method comprises the following steps: acquiring original acoustic signals collected by a main microphone array arranged in a to-be-detected area of a vehicle and reference noise signals collected by a reference microphone array arranged in a reference area of the vehicle; performing background noise filtering processing on the original acoustic signals based on the reference noise signals to obtain target acoustic signals; extracting target acoustic features corresponding to the target acoustic signals; determining a feature similarity between the target acoustic features and reference acoustic features corresponding to a current running state of the vehicle; and in a case where the feature similarity is smaller than a similarity threshold, determining a sealing performance detection result of the to-be-detected area according to the target acoustic features. The method can continuously and comprehensively detect the sealing performance of the vehicle during driving.

This utility model discloses a novel shaftless pump-driven river algae experimental device, relating to the field of aquatic ecological simulation and early warning prediction technology. It includes an experimental water tank, a propulsion pump, and vortex-generating impellers. The experimental water tank has a ring-shaped structure, with a filling space at the bottom for filling with substrate and a water passage at the top. The propulsion pump is installed inside the experimental water tank to circulate the water within the passage. Multiple vortex-generating impellers are installed inside the experimental water tank to generate vortices in the water within the passage. This device can effectively simulate the hydrodynamics and aquatic environment of a real river in a closed loop, and is compatible with river ecological physics simulations based on water level differences. It offers advantages such as realistic simulation environment, minimal bubble turbulence, low background noise, and long-term algal survival friendliness, making it particularly suitable for experimental research on algae simulation, regulation, and early warning prediction.