131 results about "Noise spectrum" patented technology

The invention discloses a self-adaptive filtering method and system for an intelligent electric energy meter, and relates to the technical field of power grid signal processing, and the method comprises the steps: obtaining a power grid voltage and current signal set collected by a target intelligent electric energy meter historically, and obtaining a signal noise spectrum data set and a noise level evaluation result through spectrum analysis and noise level evaluation; if the result exceeds a preset noise threshold value, identifying an interference type and building a noise adaptive filtering multi-channel, integrating and deploying the noise adaptive filtering multi-channel into a target intelligent electric meter to complete signal filtering test and effect evaluation, and dynamically optimizing and generating an electric energy meter adaptive filtering multi-channel based on the obtained multi-channel filtering effect index parameter; and finally, signal filtering closed-loop control is realized. The technical problem that a traditional electric energy meter is weak in filtering pertinence and cannot adapt to dynamic noise of a power grid in electric power related scenes with complex dynamic interference is solved, and the technical effects that the electric variable measurement accuracy of the electric energy meter is improved, and the adaptive capacity of the electric energy meter to different interference scenes is enhanced are achieved.

The invention discloses an order noise evaluation method and device, and relates to the technical field of noise analysis. The method comprises the following steps: acquiring a noise time-domain signal and a rotating speed time-domain signal, and obtaining a three-dimensional noise spectrum signal; determining all to-be-selected frequency points corresponding to the target rotating speed based on the three-dimensional noise spectrum signal; determining the frequency points of which the intermediate critical frequency bands of the to-be-selected frequency points meet preset requirements, and obtaining a plurality of target frequency points; based on the three-dimensional noise spectrum signal, calculating protrusion ratios corresponding to the plurality of target frequency points, and determining the maximum protrusion ratio as a target protrusion ratio; and evaluating the to-be-evaluated order noise based on the target outburst ratio. According to the method and the device, the frequency points of the intermediate critical frequency band including the order noise frequency band in the to-be-selected frequency points are determined, so that the evaluation of the whole frequency band range covering the order noise is ensured, the full-band evaluation of the influence range of the order noise is realized, the comprehensiveness of order noise rating is improved, and the accuracy of the evaluation result of the order noise is improved.

The invention relates to the technical field of voice recognition, and discloses a voice instruction recognition and cleaning control method for a sweeping robot, which comprises the following steps: synchronously reading a dust collection motor driving pulse width modulation value and a rolling brush motor load current value of the sweeping robot while acquiring an audio signal acquired by a microphone; retrieving and interpolating in a preset working condition noise spectrum mapping table according to the non-acoustic operation state data, determining a predicted mechanical noise power spectrum at the current moment, taking the predicted mechanical noise power spectrum as a priori reference, calculating an instantaneous signal-to-noise ratio of the predicted mechanical noise power spectrum and the frequency domain feature sequence, and constructing a frequency domain confidence mask; according to the method, a feedforward prediction mechanism is constructed by introducing non-acoustic prior information, and response lag of traditional acoustic posteriori estimation during sudden change of working conditions is avoided.

The invention discloses a wind turbine generator voiceprint self-adaptive detection method, system and device and a storage medium, and belongs to the technical field of wind power, and the method comprises the steps: collecting a voiceprint signal, raindrop diameter, environment humidity, environment temperature and atmospheric pressure of a wind turbine generator in real time through a sensor array; temperature and humidity coupling correction parameters are calculated based on the environment humidity, and real-time air density is obtained through correction according to an air density correction formula by means of the environment humidity, the environment temperature and the atmospheric pressure; constructing a rain intensity noise spectrum mapping model based on the raindrop diameter and the real-time air density in combination with a raindrop vertical fragmentation merging effect compensation algorithm; performing rain noise suppression on the voiceprint signal of the wind turbine generator by adopting a depth spectrum subtraction algorithm in combination with the rain intensity noise spectrum mapping model and the dynamic suppression factor to obtain a clean voiceprint signal; and matching the clean voiceprint signal with a preset wind turbine generator fault voiceprint feature library to complete wind turbine generator voiceprint adaptive detection.

The invention relates to the technical field of audio signal processing, and discloses an industrial noise identification method and system, and the method comprises the steps: obtaining an audio signal, and carrying out the time-frequency decomposition, and obtaining preliminary decomposition data; classifying the coupling features of the preliminary decomposition data to obtain a coupling region boundary value; if the boundary value of the coupling region exceeds a preset boundary threshold value, performing filtering processing to obtain separated noise spectrum data; calculating an overlapping proportion of the separated noise spectrum data and a preset target sound; if the overlapping proportion causes extraction deviation, extracting dynamic change characteristics of the separated noise spectrum data and fusing the dynamic change characteristics into a spectrum extraction process to obtain an accurate noise spectrum; calculating an intensity value according to the accurate noise spectrum, and determining an intensity evaluation result; and comparing the intensity evaluation result with a preset pollution threshold, calculating a noise pollution degree and outputting a noise identification result. The method is suitable for industrial environment noise monitoring, and can accurately extract the noise spectrum.

The invention provides a polishing end point detection method, chemical mechanical polishing equipment and a storage medium, and belongs to the field of chemical mechanical polishing. The method comprises the steps that a reflection spectrum of the surface of a wafer in the chemical mechanical polishing process is obtained; correcting the reflection spectrum by adopting a preset correction coefficient to obtain a corrected reflection spectrum; dividing the corrected reflection spectrum into a dark noise spectrum and a to-be-measured spectrum based on a comparison result of the corrected reflection spectrum and a corresponding threshold value; determining the reflectivity of the surface of the wafer based on the to-be-measured spectrum, the dark noise spectrum, the reference spectrum and a preset reference spectrum reflectivity; the wafer thickness is determined using the reflectivity of the wafer surface to detect a polishing endpoint based on the wafer thickness. The terminal point detection accuracy is improved.

The application relates to the technical field of system-in-package, and discloses a functional chip SIP (System in Package) system-in-package method and system. The method constructs a reduced-order discrete thermal state predictor through multi-order exponential attenuation fitting, generates a DVFS gear-noise hazard degree spectrum mapping table based on a synchronous switching noise spectrum and an ADC noise sensitivity curve, generates a multi-DVFS working condition robust grounding network topology by optimizing a narrow bridge connection structure parameter by using a sequential quadratic programming, quantizes equivalent noise interference amounts of each DVFS gear on an ADC chip, and jointly optimizes DVFS gear selection and power consumption upper limit distribution under a rolling time domain mixed integer quadratic programming framework, simultaneously performs online model correction through exponential weighted moving average and Kalman filtering, and realizes cooperative satisfaction of thermal constraints and noise constraints.

The invention relates to the technical field of mining machinery intelligent monitoring, and discloses a remote monitoring system and method based on a crusher. According to the system, an original current waveform and a bearing voiceprint signal in a starting stage are collected through an initial state sensing unit, a current waveform deviation spectrum is generated, sound energy of a specific frequency band is extracted, and an initial state data set is formed through fusion; the dynamic operation analysis unit monitors a power fluctuation period, a torque change slope and a material flow noise spectrum in a steady state, and generates a real-time operation state flow; the self-adaptive regulation and control unit identifies an abnormal correlation mode of power and torque, starts fine adjustment of the feeding speed when the torque slope exceeds a threshold, and dynamically adjusts an instruction according to real-time feedback of noise characteristic frequency band energy. According to the scheme, early diagnosis of hidden faults of the equipment and predictive smooth control of the material blocking risk are realized, and the equipment reliability and the production continuity are improved.

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.

A method and a decoder for generating concealment audio frame of an audio signal. The method includes performing a frequency domain analysis of a sequence of previously decoded audio signal to obtain a frequency spectrum and identifying peaks in the spectrum. The method further includes estimating a relative energy between the noise spectrum and the complete spectrum, determining an attenuation of the noise spectrum based on the relative energy, and applying the attenuation to the noise spectrum. The method includes applying an inverse transform to time domain on an error concealment spectrum, that includes the peaks and the attenuated noise spectrum.

A method and a decoder for generating concealment audio frame of an audio signal. The method includes performing a frequency domain analysis of a sequence of previously decoded audio signal to obtain a frequency spectrum and identifying peaks in the spectrum. The method further includes estimating a relative energy between the noise spectrum and the complete spectrum, determining an attenuation of the noise spectrum based on the relative energy, and applying the attenuation to the noise spectrum. The method includes applying an inverse transform to time domain on an error concealment spectrum, that includes the peaks and the attenuated noise spectrum.

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 discloses a noise logging sound source point signal extraction method. The method comprises the following steps: acquiring noise spectrum data; global background noise is calculated after global stable background well section noise data is selected from the noise spectrum data, and the global background noise in the noise spectrum data is eliminated to obtain spectrum data without background noise; selecting a sound source layer section and a processing layer section from the spectrum data without background noise by using a half amplitude point method, and processing the spectrum data of the processing layer section through a sound conduction model to obtain conduction noise of the processing layer section; and processing layer section conduction noise in the spectrum data without background noise is eliminated to obtain stratum noise spectrum data, and extraction is completed.

This invention provides a method, device, electronic equipment, and storage medium for active noise reduction in vehicles. During vehicle operation, the method searches for a target amplitude in a pre-defined mapping relationship between the current motor speed and the target amplitude. A noise reduction signal is generated based on the current motor frequency, the target amplitude, and the reverse motor phase to cancel out gear-induced noise, thus actively reducing vehicle noise. This method eliminates the need to adjust the torque distribution between the front and rear electric drive systems. Instead, it queries the corresponding noise spectrum based on the current motor speed and plays the inverse noise reduction signal for active noise reduction. This improves the suppression of whistling noise under heavy loads. Because this invention does not require adjusting the torque distribution between the front and rear electric drive systems, it does not affect driving safety.

This invention provides an electromagnetic noise analysis apparatus and method that achieves both reduced analysis time and improved analysis accuracy. [Solution] The electromagnetic noise analysis device 1 includes: a noise spectrum analysis unit that performs frequency-axis noise analysis on any observation point of a power conversion circuit in which at least two switches are connected between power supplies, representing each switch as a voltage source or current source on the frequency axis; a voltage source / current source noise source parameter generation unit that generates a parameter table for representing switching operation as a voltage source or current source on the frequency axis according to operating conditions including power supply voltage, gate resistance of each switch, or current; a worst-case condition extraction unit that extracts phase relationships and current amounts in which the noise amount can become the worst-case condition in the time-axis operation of each switch based on control; and a worst-case condition noise source model generation unit that sets the worst-case condition noise source parameters using the extraction results by the worst-case condition extraction unit.

The invention discloses an active sound production system and method for optimizing door closing sound quality, and relates to the field of simulation testing, a multi-dimensional sensing array module comprises a distance sensor, a three-axis acceleration sensor, a distributed microphone array and a temperature and humidity sensor, the sensors synchronously collect data, the data are transmitted through a CAN bus, and the timeliness and consistency of the data are ensured; the environmental acoustic modeling module is used for carrying out noise spectrum analysis on microphone signals, evaluating a vehicle door motion state, processing distance and acceleration data, calculating a temperature correction coefficient, dynamically adjusting sound pressure parameters, periodically updating an environmental parameter matrix and reflecting acoustic characteristics under different working conditions; and the PID-fuzzy hybrid algorithm module adopts a PID and fuzzy logic fusion framework, presets a target frequency, a maximum sound pressure level and a door closing speed threshold value, and calculates frequency, sound pressure and speed deviation, and the fuzzy logic module dynamically adjusts PID parameters according to the noise level, weights and superposes a proportional term, an integral term and a differential term, and is used for regulating and controlling the door closing sound quality.

The invention discloses an internal arteriovenous fistula portable intelligent auscultation instrument for hemodialysis, and relates to the technical field of medical equipment. An alarm, three auscultation result indicating lamps with different colors, an equipment switch and an electric quantity indicating lamp are arranged on the auscultation instrument main machine, an equipment power supply, a control module, a wireless data transmission module and an AI noise recognition chip are arranged in the auscultation instrument main machine, and an auscultation head and a conduction tube are arranged on the outer side of the auscultation instrument main machine. And an auxiliary fixing mechanism is arranged on the stethoscope head. A noise reduction acoustic filter screen is arranged in the auscultation head to accurately filter interference, a signal amplification module at the tail end of a conduction tube amplifies weak blood flow sound, an AI noise recognition chip with a clinical noise spectrum pre-recorded is matched, the internal fistula noise state can be automatically recognized without depending on professional auscultation experience, visual feedback is achieved through a three-color auscultation result indicator lamp, linkage early warning is matched with an alarm, and the internal fistula noise state can be automatically recognized. Common medical care can quickly complete clinical screening, and a patient can also perform self-examination at home, so that the risks of missed judgment and misjudgment are thoroughly avoided.

The invention belongs to the field of marine acoustics, and discloses a wind speed-based multi-stage modeling regression marine environmental noise model modeling method, which comprises the following steps of: firstly, acquiring and matching marine noise and wind speed data, and extracting a noise power spectrum; fitting the noise spectrum into gamma distribution, and extracting shape and scale parameters as physical statistical characteristics; in the first stage, Gaussian process regression is utilized to establish mapping from wind speed to distribution parameters; in the second stage, the distribution parameters and the wind speed serve as input, a mixed kernel support vector regression model fusing a Wenz empirical physical kernel and an RBF data kernel is adopted, and a full-band noise spectrum is predicted. According to the method, a complex prediction problem is decomposed through a framework of'physical statistical feature guidance ', physical priori and data-driven learning are effectively fused, prediction precision, generalization ability and robustness of the model under the condition of data scarcity are remarkably improved, and a high-precision noise prediction tool is provided for applications such as ocean wind field monitoring and the like.

This invention discloses a porous Helmholtz resonator with adaptively adjustable sound absorption frequency band, belonging to the fields of noise control and virtual reality technology. It comprises a sound-absorbing structure consisting of a rotating perforated panel, a fixed perforated panel, and a perforated porous material plate arranged sequentially from top to bottom, as well as an adaptive adjustment system composed of a sound pressure sensor, a controller, and a motor. The motor drives the rotating perforated panel to rotate via gear transmission, changing the perforation overlap area; the perforated porous material plate compensates for acoustic impedance, maintaining sound absorption performance. The controller pre-stores spectral data at different rotation angles and selects the optimal rotation angle by comparing the real-time noise spectrum with the pre-stored data. This invention achieves adaptive adjustment of the sound absorption frequency band, maintains a high sound absorption peak value over a wide parameter range, is suitable for large-area deployment, has a compact structure, and low cost, and can be used for noise control and auditory virtual scenes.

The application discloses a kind of based on real-time global illumination and grating hybrid acceleration ultra-high voltage station rendering method, it is related to ultra-high voltage station inspection simulation technical field, including the following steps: in strong electromagnetic interference environment, by adaptive electromagnetic interference filtering algorithm is combined with global illumination probe dynamic interpolation compensation algorithm, dynamic adjustment illumination sampling frequency and insert pre-computed global illumination data.The application is by adaptive electromagnetic interference filtering and illumination sampling dynamic compensation mechanism, effectively suppresses the high-frequency jitter of illumination data caused by strong electromagnetic noise, can according to the noise spectrum characteristics of real-time acquisition intelligent adjustment global illumination probe sampling frequency, and is combined with material perception illumination interpolation algorithm, ensure that metal and insulator surface under different interference intensity all present continuous, smooth illumination performance, so that ultra-high voltage station still can maintain stable visual output under strong electromagnetic interference environment, guarantee the reliability and authenticity of inspection simulation process.

The present application relates to a kind of sound barrier noise reduction structure and its design method, comprising: the high-frequency valley of high-frequency noise of the measured noise spectrum is determined as the valley frequency of the high-frequency sound insulation amount of the resonant unit, the low-frequency peak of low-frequency noise is determined as the peak frequency of the low-frequency sound insulation amount of the composite waveguide layer, according to the number of low-frequency peak determines the number of Helmholtz cavity;According to valley frequency, obtain the thickness of micro-perforated plate layer, the diameter of small hole on micro-perforated plate layer, the thickness of hollow cavity layer and its cross-sectional size parameter relationship formula, so as to optimize the selection of relevant parameters;According to each peak frequency, respectively calculate and obtain the volume of corresponding Helmholtz cavity, and the effective area, cross-sectional length relationship of its corresponding throat pipe, so as to optimize the selection of effective area.The structure designed by resonance system controls high-frequency noise, utilizes the Helmholtz cavity of composite waveguide layer to control low-frequency noise, realizes selective sound insulation in large frequency range.

This invention proposes a design method for a full-band compact hybrid EMI filter circuit based on current feedback. The method includes: constructing an electromagnetic interference test circuit to obtain the common-mode EMI spectrum required for attenuation by the PWM converter, and establishing a high-frequency equivalent circuit for the PWM converter; obtaining the optimal hybrid EMI filter topology based on the high-frequency equivalent models of active and passive EMI filter circuits and the noise attenuation characteristics of the hybrid EMI filter circuit topology; designing the active EMI filter topology and its high-frequency equivalent model based on the noise cancellation principle of the active EMI filter and the common-mode EMI spectrum; designing the active EMI filter topology based on the noise cancellation principle of the active EMI filter and the common-mode EMI spectrum; designing the passive EMI filter structure based on the common-mode EMI noise spectrum after adding the active EMI filter; and designing the hybrid EMI filter circuit based on the hybrid EMI filter topology, the active EMI filter topology, the passive EMI filter structure, and the high-frequency equivalent models of the active and passive EMI filter circuits.

The invention relates to the technical field of vehicle-mounted communication, in particular to a communication interconnection method and system applied to a vehicle-mounted navigator. The method comprises the following steps: collecting a rolling noise signal of a tire through a chassis microphone of a vehicle-mounted navigator, recording the rolling noise signal as a noise frequency spectrum reference value when approaching a tunnel is detected, and identifying a tunnel entrance moment; calculating the difference between the tire noise signal after entering the tunnel and the noise spectrum reference value based on the tunnel entrance moment, and extracting a newly added formant frequency value and formant sharpness value; and calculating the cross section area of the tunnel according to the formant frequency value, judging the traffic flow density in the tunnel according to the formant sharpness value, and combining the cross section area of the tunnel and the traffic flow density in the tunnel to form tunnel environment characteristic parameters. According to the method, the communication signal intensity distribution of each position in the tunnel can be predicted in advance by analyzing the resonance characteristics of the tire noise.

The technology described herein is directed towards collecting detailed noise spectra measured from one or more servers (or similar devices) via an array of microphones, which can be positioned to capture the noise spectra in a suitable test environment. Based on the noise spectra, a metasurface of unit cells based on the principles of Helmholtz resonators, is designed. The noise spectra are maintained in a data store / database, along with hardware feature data of the measured device. The database returns the server noise profile, from which a metasurface's unit cell design parameters suitable for server noise suppression are configured, e.g., printed by a 3D printer and deployed for use with the server. The database can be used for a non-measured server with similar hardware feature data to measured servers, to estimate the noise peaks of the non-measured server from which a noise-canceling metasurface's unit cell parameters can be determined.

The invention discloses an air duct assembly and air treatment equipment, the air duct assembly comprises a main body part, the main body part defines an airflow channel extending in the first direction, the main body part further defines or participates in defining a plurality of silencing cavities, and each silencing cavity communicates with the airflow channel through at least one silencing hole; the air channel assembly comprises at least one set of silencing sections, each set of silencing sections comprises at least two silencing cavities located in different silencing rings, the multiple silencing cavities corresponding to each set of silencing sections are arranged in the circumferential direction of the airflow channel at intervals, the difference value of the resonant frequencies of any two silencing cavities in each set of silencing sections is U1, and U1 is larger than or equal to 0 and smaller than or equal to 100 HZ. According to the air duct assembly, the multiple noise reduction cavities are arranged, so that the air duct assembly can cover a wider noise frequency spectrum, the multiple noise reduction cavities with the same or similar resonance frequencies are formed in the circumferential direction of the airflow channel, noise in the whole circumferential direction can be efficiently eliminated, and the noise reduction effect of the air duct assembly is further improved.

This application relates to a method, apparatus, computer device, and computer-readable storage medium for generating fiber Raman spectroscopy preprocessing models. The method includes: determining the true noise spectrum and random noise of the target object; generating a clean spectrum corresponding to the true noise spectrum based on a spectral synthesis method; generating fluorescence background data corresponding to the true noise spectrum based on a fluorescence background synthesis strategy; training a model using the true noise spectrum, clean spectrum, and fluorescence background data to obtain a trained background removal model; and training a multi-channel model based on random noise and clean spectrum to obtain a trained noise removal model. By employing this method, a reliable model processing foundation can be provided for background separation processing of Raman spectral signals and for collaborative denoising in both the spectral and frequency domains, improving the generation efficiency and quality of training datasets and achieving efficient and high-quality spectral processing in complex environments.

The invention discloses a semi-automatic test method for an energy storage prefabricated cabin, and belongs to the technical field of intelligent testing, and the method comprises the steps of test system construction, semi-automatic testing, multi-physics coupling test analysis and test report generation. According to the scheme, a semi-automatic test process is constructed, automatic acquisition and manual verification are combined, a load sequence and an acquisition instruction are preset in an automatic stage, three-dimensional temperature gradient distribution is generated, a noise spectrum and heat dissipation efficiency are weighted A, and fan rotating speed strategy adjustment, noise source positioning and abnormal data labeling are performed in a manual verification stage. A data foundation is laid for multi-physics field analysis; dynamically adjusting noise confidence and sample weight, generating an adversarial fusion threshold, adaptively adjusting the base classifier weight and the sample weight, establishing a multi-physics field coupling test model, outputting a heat dissipation performance level, a noise compliance judgment result, a coupling risk level and a heat dissipation-noise correlation index; and decision support is provided for optimization and safe operation of the prefabricated cabin.

A method for diagnosing the noise level of a transformer comprises: a step of acquiring a frequency spectrum of noise from a stacked iron core 21 contained in a transformer, the stacked iron core 21 being formed by stacking electrical steel laminations; a step in which, for the calculation of the excitation vibration of the stacked iron core 21, the transverse moduli of elasticity are determined in two planes, each including a stacking direction of the stacked iron core 21; a step in which the excitation vibration for the stacked iron core 21 is calculated using a constitutive equation that includes an elasticity matrix comprising the determined transverse moduli of elasticity as elements, and a frequency spectrum of an excitation vibration of the stacked iron core 21 is acquired;a calculation stage of the difference between the excitation noise spectrum of the stacked iron core 21 and the excitation vibration frequency spectrum of the stacked iron core 21 as a differential spectrum; and a transformer noise level diagnostic stage based on the differential spectrum.

This invention relates to a method for separating vibration and flow noise in the underwater noise spectrum of a ship propeller, comprising: constructing a "frequency label" for vibration noise by fabricating two propeller models with identical geometry but significantly different material properties; a dual-model difference stage: calculating the absolute difference in the noise spectra of the two models and generating a vibration noise mask based on modal analysis results; a blind source separation stage: for the residual signal after difference, using an improved Independent Component Analysis (ICA) algorithm to further separate residual interference by utilizing the statistical independence of vibration noise; introducing a convolution kernel function in this stage to enhance the algorithm's adaptability to time-delayed signals; and introducing Cepstrum analysis technology to perform phase correction on the complex spectrum of the replacement frequency band. This method solves the significant shortcomings of existing noise control technologies in the coupling separation of vibration and flow noise, enabling the separation of the components of underwater noise from ship propellers, obtaining the noise components caused by blade vibration and the flow noise components separately.

For example, an apparatus may include an input to receive digital radar Receive (Rx) information corresponding to radar Rx signals, the digital radar Rx information having a first number-of-bits-per-sample; and a noise-shaping quantizer configured to generate quantized radar Rx information by quantizing the digital radar Rx information. For example, the quantized radar Rx information may have a second number-of-bits-per-sample less than the first number-of-bits-per-sample. For example, the noise-shaping quantizer may be configured to generate the quantized radar Rx information having a non-uniform quantization noise spectrum, which has a non-uniform distribution in a frequency domain. For example, the apparatus may include an output to provide the quantized radar Rx information.