Noise Suppression Effect Research Articles

Π-shaped pixel pattern for shift multiplexing surface holograms in holographic data storage

In this study, a method for shift multiplexing surface holograms was proposed for data storage systems. Shift multiplexing of surface holograms is inhibited by noise specific to Raman–Nath diffraction. We proposed a model to analyze the influence of noise. Subsequently, we proposed a method for noise suppression to arrange signal and reference pixels in a shape similar to the Greek letter “Π.” The proposed method is generally applicable to thin holograms in which Raman–Nath diffraction occurs. The effectiveness of noise suppression using the proposed method was experimentally demonstrated. We theoretically estimated that a shift multiplexing surface holographic data storage system using the proposed method could achieve a significantly higher data transfer rate than conventional optical discs while maintaining a comparable storage density.

A novel wafer defocus measurement method for spot-scanning imaging system using laser triangulation

Abstract For spot scanning dark-field scattering technology, the defocus caused by the change in wafer surface height decreases the defect detection rate and size measurement repeatability. The demand for accurately and rapidly measuring the wafer surface height online is becoming increasingly urgent. The defect detection system integrates scattering, reflection, film thickness, and topography defect detection channels. The integration of laser-triangulation-based defocus measurement into the bright-field optical path is proposed. The laser beam is directed onto the surface of the wafer, and the reflected light is transmitted through a lens onto the photosensitive surface of a four-quadrant detector. This detector captures both the strength and position of the reflected signal simultaneously. In this paper, a triangulation-modified model is established to obtain the height of each inspection spot on the wafer surface through the position signal of the reflected image. When the signal-to-noise ratio of the simulated reflection image position is 20 dB, the signal-to-noise ratio of the height measurement resolved by the triangulation-modified model is 41 dB, and the measurement error is less than 0.2 μm, indicating that the model has a noise suppression effect. The spot-scanning imaging system is established, and the height measurement results of the triangulation measurement model are verified using a laser interferometer. Within the travel range of 69 μm, the system has a measurement accuracy better than ±1 μm and a measurement repeatability better than ±0.2 μm, which meet the measurement requirements of the spot-scanning imaging system. The system is utilized for defect detection and defocus measurement of the wafer surface, along with the motion mechanism, to accurately and rapidly obtain the height distribution of the wafer surface.

Modal analysis and structural noise control of vehicle body frame

The structural noise inside the vehicle cabin is mainly low-frequency vibration, which is closely related to the modal characteristics of the vehicle frame. The finite element method was used to simulate and calculate the body frame under free modal conditions, and the first four effective modal shapes were obtained. The calculation error of the natural frequencies was verified through modal experiments. Taking structural stiffness into account, a sound-structure coupled model was established. The suspension connection point was selected as the excitation point, and a one-way dynamic load was applied to obtain the noise and vibration responses of the front and rear rows. Based on the modal analysis results, the top-roof reinforcement scheme was adopted to verify the noise suppression effect of the structure. The results show that the optimized structure can effectively suppress structural noise, which plays an important role in improving the NVH characteristics.

Research on Typical Fault Diagnosis of Gear based on GHM Multiwavelet Transform and MCKD Algorithm

Background: Gear is the key part of the transmission part of mechanical equipment, which has a high failure rate under complex working conditions or long-term operation, directly affecting the reliability of mechanical equipment. To realize online monitoring of gears and predict gear faults, whether the diagnosis of typical gear faults is accurate and timely is a key link, so it is necessary to study the diagnosis of typical gear faults. Objective: This paper aims to propose a method that can effectively diagnose typical faults of gears and is easy to program, which is beneficial to realize online monitoring of rotating machinery equipment faults. Method: A typical gear fault diagnosis method based on GHM multiwavelet transform and maximum correlation kurtosis deconvolution algorithm (MCKD) is proposed in this paper. The measured vibration signal is decomposed into components with multiple scale spaces and frequency bands through the GHM multiwavelet transform. Then, the MCKD algorithm is run to suppress the noise of GHM multiwavelet transform coefficients, and the periodic components containing fault information are retained and reconstructed. The typical faults such as gear pitting and broken teeth are tested. Results: GHM multiwavelet transform combined with MCKD algorithm can accurately locate the frequency band containing fault information from the vibration signal with multiple modulations, double sideband, and multi-frequency interference and effectively extract the fault frequency and its frequency multiplication. The root means a square error of the extracted fault frequency is 0.08. This method has a good noise suppression effect and high accuracy in extracting fault frequency. Conclusion: The method proposed in this paper is helpful in realizing automatic programming of gear fault diagnosis and is of great significance in realizing real-time monitoring and online diagnosis of rotating machinery equipment faults. More related patents will appear in the future.

GA-BP-Based Low-Noise FBG Hydroacoustic Monitoring System with Reference Sensor.

To address the issue of harsh marine background noise impacting the monitoring signal of fiber-optic hydrophones, we propose a low-noise fiber Bragg grating (FBG) hydroacoustic monitoring system with a reference sensor based on genetic algorithm backpropagation (GA-BP). Through theoretical analysis, we deduce the noise suppression steps of the GA-BP algorithm based on the reference sensor and construct train and test sets based on the data from the reference sensor and monitoring sensor at different times, optimizing the GA-BP algorithm to find the best fitting results and thereby obtaining the low-noise monitoring signal. Experimental results from the anechoic tank show that the proposed method can suppress background noise interference on effective signals and that the suppression effect improves as the background noise increases. The sound pressure sensitivity ranges from -173.76 dB to -171.33 dB at frequencies of 8 kHz to 12 kHz, with a response flatness of less than 2.43 dB. The noise suppression effect is obvious under the condition of poor signal-to-noise ratio (SNR), which can reach more than 18.3 dB. The advantages of the proposed algorithm in array signal processing are further demonstrated by the directivity experiment, which proves that the algorithm has a great potential for engineering applications in harsh marine environment.

Prior image-based generative adversarial learning for multi-material decomposition in photon counting computed tomography

BackgroundPhoton counting detector computed tomography (PCD-CT) is a novel promising technique providing higher spatial resolution, lower radiation dose and greater energy spectrum differentiation, which create more possibilities to improve image quality. Multi-material decomposition is an attractive application for PCD-CT to identify complicated materials and provide accurate quantitative analysis. However, limited by the finite photon counting rate in each energy window of photon counting detector, the noise problem hinders the decomposition of high-quality basis material images. MethodsTo address this issue, an end-to-end multi-material decomposition network based on prior images is proposed in this paper. First, the reconstructed images corresponding to the full spectrum with less noise are introduced as prior information to improve the overall signal-to-noise ratio of the data. Then, a generative adversarial network is designed to mine the relationship between reconstructed images and basis material images based on the information interaction of material decomposition. Furthermore, a weighted edge loss is introduced to adapt to the structural differences of different basis material images. ResultsTo verify the performance of the proposed method, simulation and real studies are carried out. In simulation study of structured fibro-glandular tissue model, the results show that the proposed method decreased the root mean square error by 67 % and 26 % on adipose, 66 % and 28 % on fibroglandular, 52 % and 8 % on calcification, compared to butterfly network and dual interactive Wasserstein generative adversarial network. ConclusionExperimentally, the proposed method shows certain advantages over other methods on noise suppression effect, detail retention ability and decomposition accuracy.

Numerical analysis and experimental study of membrane-type acoustic metamaterial plate with X-shaped pendulum arm and cylindrical mass blocks

Membrane-type acoustic metamaterials have a favorable noise suppression effect. Hence, a membrane-type acoustic metamaterial plate (MAML) with an X-shaped pendulum arm and cylindrical mass blocks (CMB) was proposed in this paper. The theoretical model based on spring–mass systems and numerical simulation models of the membrane-type acoustic metamaterial cell (MAMC) were established under fixed and periodic boundary conditions to reveal the noise attenuation mechanism quantitatively, and the necessity of the CMB is discussed. Based on the results, it can be observed that the normal displacement of the membrane is nearly zero when the noise frequency is at the peak of the sound transmission loss (STL) curve. However, when the frequency is at the valley of the STL curve, the displacement is nonzero and fluctuates significantly. Meanwhile, by comparing the STL curves with and without the CMB, it was found that the MAMC performance is improved effectively by the CMB at low frequencies. The effective mass density of MAMC was found to be negative. To verify the accuracy of numerical calculations, an impedance tube experiment was conducted. Finally, orthogonal experiments were designed to describe the effects of the structural parameters a, l, and t on the effective bandwidth [Formula: see text], peak frequency [Formula: see text], and comprehensive index [Formula: see text] and to obtain the optimal structural parameter combinations for different indexes. This work further contributes to applying and developing the membrane-type acoustic metamaterial.

Model-free adaptive predictive control with unscented Kalman filter for hovercraft speed and heading stabilization

This paper develops a novel unscented Kalman filter-model free adaptive predictive control (UKF-MFAPC) method for an underactuated hovercraft speed and heading stabilization under the influence of measurement noise. First, the proposed method is based on the compact form dynamic linearization (CFLD) technique, which involves an analysis of the tight format dynamic linearization method. This approach specifically addresses the unique non-real-time scalability of the heading control subsystem, rendering the CFDL method unsuitable. Through redefining the linear combination of lateral velocity and heading as output to fulfill all assumptions of CFDL methods, this scheme effectively mitigates the lateral velocity vibration problem of the hovercraft. Secondly, this controller introduces the measurement noise during the data collection process into the optimization function and combines the unscented Kalman filtering method with data-driven models, the influence of error suppression noise on the controller is suppressed, ensuring that the output can still be controlled within a certain range of expected values. This paper also delves into the convergence of tracking errors and examines the stability of bounded inputs and outputs. Finally, the noise suppression effect and stability of the UKF-MFAPC scheme are demonstrated through a comparative analysis of simulation results with proposed model-free methods.

Noise suppression method for OPGW transmission line galloping monitoring by using adjacent FBG sensors

To solve the problem of transmission line galloping monitoring for optical power grounded waveguides (OPGWs) in external field environments, we propose a low-noise monitoring array based on adjacent sensors with low reflectivity fiber Bragg grating (FBG). We analyze the interference signal models for adjacent FBG sensors, and based on them, a noise suppression method by using adaptive filter input is constructed. Then we simulate the noise suppression effect of the proposed algorithm under different noise conditions. Finally, we deploy the low-noise OPGW transmission line galloping monitoring system based on low reflectivity FBGs in China’s western autonomous prefecture with a 220 kV transmission line. The experimental results show that, after adaptive filtering using adjacent sensors, the average noise power spectral density is reduced by 6.5 dB, and the algorithm optimizes the monitoring intensity spectrum. Oscillation events of about 100 m can be clearly observed within the monitoring interval. It creates certain conditions for further improving the typical event classification data processing and pattern recognition database for OPGWs and demonstrates promising prospects for engineering applications.

Influence of EOM sideband modulation noise on space-borne gravitational wave detection

Clock noise is one of the dominant noises in the space-borne gravitational wave (GW) detection. To suppress this noise, the clock noise-calibrated time-delay-interferometry (TDI) technique is proposed. In this technique, an inter-spacecraft clock tone transfer chain is necessary to obtain the comparison information of the clock noises in two spacecraft, during which an electro-optic-modulator (EOM) is critical and used to modulate the clock noise to the laser phase. Since the EOM sideband modulation process introduces the extra modulation noise, it may limit the experimental demonstration of the suppression effect of the clock noise, and further affect the space-borne GW detection. To solve this problem, it is significant to put forward the modulation noise requirement and test whether the experimental components meet or not. In this work, based on the typical Michelson TDI algorithm and the fundamental noise requirement of GW detectors, the analytic expression of the modulation noise requirement is strictly derived, relaxing the specification compared to the commonly used rough assessments. Furthermore, a method is provided to experimentally test EOM modulation noise, and a commercial EOM (iXblue-NIR-10 GHz) is tested. The experimental results show that it can meet the requirement of the typical GW detection mission LISA in the whole scientific frequency bandwidth by taking the optimal combination of the data streams.

Study of low-frequency noise suppression effect inside acoustic cavities by applying piezoelectric nonlinear energy sink

In this paper, the piezoelectric nonlinear energy sink (NES) is used to suppress the radiated noise from a thin plate, and the targeted energy transfer (TET) characteristics and mechanism of the coupled system of two piezoelectric NESs and a thin plate are analyzed, and the coupling model of the system with the acoustic cavity, rectangular thin plate and piezoelectric NES is established. The parameters of the piezoelectric NESs are adjusted according to the excitation amplitude, and then applied to the rectangular thin plate. The numerical results show that the piezoelectric NES causes the system to undergo strongly modulated response (SMR) and the resonance peak of radiation noise is effectively suppressed. It provides a new technique for passive control of low-frequency noise.

Theoretical and numerical investigation into the suppressing mechanism of radiated noise in an ABH-cavity system

The problem of radiated noise of a coupling system between acoustic space and flexible structure is very common in practical applications. In this paper, the acoustic black hole (ABHs) structure is used for reducing the radiated noise of the plate-cavity system as an efficient passive control technology. The suppression mechanism of the ABH-cavity system is investigated. Theoretical analysis shows that enhanced radiated noise suppressing effect can be obtained by rearranging the numbers and locations of ABHs compared to its uniform counterpart at cavity modal frequencies. Due to this suppression mechanism, ABH structure exhibits a reduced radiation efficiency of the panel, which can be explained by the wavenumber analysis that lots of high wavenumber components are generated and effective wavenumbers in the radiation region are reduced.

Numerical Study on Aerodynamic and Aeroacoustic Performances of Bioinspired Wings

Noise control has become one of the key issues to be considered in modern aeronautical machinery design. Many efforts have been devoted to noise reduction of airfoils and wings, including traditional flow control methods. In fact, some animals in wild nature exhibit superior aerodynamic and aeroacoustic performance, providing novel ideas for solving this engineering problem. In this research, bionic technology is used to obtain quiet and efficient wing. Inspired by the owl’s wing, we propose two bionic configurations, one coupled with leading edge waves and trailing edge serrations. The Large Eddy Simulation and the Ffowcs-Williams and Hawkings equation is applied to simulate the aerodynamic and aeroacoustic characteristics of wings at low-Reynolds number flow. Numerical results demonstrate that the bioinspired wings have excellent aerodynamic performances and remarkable lower overall sound pressure level compared to NACA 0016 which has similar relative thickness. In addition, the unsmooth structure of leading edge waves and trailing edge serrations provide an additional 4.27 dB noise suppression effect, with little impact on aerodynamic characteristics at small angle of attack. The detailed analysis reveals that, due to the special owl-based profile, the flow around two bioinspired wings is mainly turbulent on the upper and lower surfaces, and no laminar separation bubble is detected at the trailing edge. Moreover, the unsmooth structure modifications successfully weaken the scale and scope of coherent vortex structures. These factors contribute to reducing the associated pressure fluctuation, thereby controlling the aeroacoustic noise of wing. Consequently, a coupled bionic wing is presented with the excellent aerodynamic and aeroacoustic characteristics. The conclusions are envisioned to be beneficial to the design of new generation low-noise aeronautical machinery.

Chaotic signal denoising based on energy selection TQWT and adaptive SVD.

Aiming at the problem of denoising chaotic signals with low signal-to-noise ratio and unknown dynamic system parameters, a new chaotic signal denoising algorithm is proposed, which combines adjustable Q-factor wavelet transform (TQWT) and adaptive singular value decomposition (ASVD). This method uses TQWT to decompose the noisy chaotic signal. According to the maximum wavelet entropy theory and energy threshold rule, the subband of TQWT is accurately divided into signal subband and noise subband. For noise subbands, adaptive SVD is used to denoise them, to achieve preliminary denoising. In ASVD, the standard deviation of the singular value subset is used to determine the effective reconstruction order to improve the noise suppression effect. To further remove noise in the signal subband, TQWT reconstruction is performed on the preliminarily denoised signal, and ASVD is used to denoise the reconstructed signal again to obtain the chaotic signal after secondary denoising. Chua's simulated signal and four kinds of underwater radiated noise measured by TQWT-ASVD were denoised, and compared with the SVD denoising method, TQWT denoising method, complete ensemble empirical mode decomposition with adaptive noise and threshold denoising method (CEEMDAN-WT) and modified ensemble empirical mode decomposition combined with least squares denoising method (MEEMD-LMS), The experimental results show that the TQWT-ASVD method can reduce the noise of chaotic signals more effectively. Compared with SVD, TQWT, CEEMDAN-WT, MEEMD-LMS, and Chua's signal denoising method, the signal-to-noise ratio (SNR) of this method increased by 23.22%, 26.46%, 18.79%, 16.11% the root mean square error (RMSE) decreased by 32.53%,39.48%, 30.96%, 27.94%, and the row entropy (PE) decreased by 40.44%, 41.96%, 22.78%, 20.59%; After reducing the radiation noise of cargo ships, the PE value of this method is reduced by 13.91%, 10.18%, 10.88%, 8.68% respectively, and the FE value is reduced by 33.66%, 31.42%, 26.98%, 21.32% respectively.

Fading noise suppression method of Ф-OTDR system based on non-local means filtering

Distributed optical fiber acoustic sensing (DAS) is a kind of optical fiber sensing system based on phase sensitive optical time domain reflection technology (Ф-OTDR). It has the characteristics of high sensitivity, long distance and real-time detection, and has been widely used in the positioning and monitoring of various engineering events. However, the high coherent detection light source used in the Ф-OTDR technology will produce coherent fading phenomenon in the fiber, which causes fading noise. This will seriously affecting the monitoring effect of the DAS system. Therefore, in order to address the fading noise problem in DAS system, a system fading noise suppression method based on non-local means filtering is proposed, which can effectively suppress the system fading noise in the signals and improve signal-to-noise ratio while preserving the characteristics of the target event signals. The experimental results show that the proposed method has better DAS system noise suppression effect in the face of different intensities and types of noise interference. Further, the proposed method is compared with EEMD, wavelet and outlier noise suppression methods. The results show that the noise suppression effect is significantly better than other methods, and the signal-to-noise ratio is improved by more than 30%, which verifies the effectiveness and superiority of the proposed method.

Non-Local SAR Image Despeckling Based on Sparse Representation

Speckle noise is an inherent problem of synthetic aperture radar (SAR) images, which not only seriously affects the acquisition of SAR image information, but also greatly reduces the efficiency of image segmentation and feature classification. Therefore, research on how to effectively suppress speckle noise while preserving SAR image content information as much as possible has received increasing attention. Based on the non-local idea of SAR image block-matching three-dimensional (SAR-BM3D) algorithm and the concept of sparse representation, a novel SAR image despeckling algorithm is proposed. The new algorithm uses K-means singular value decomposition (K-SVD) to learn the dictionary to distinguish valid information and speckle noise and constructs a block filter based on K-SVD for despeckling, so as to avoid strong point diffusion problem in SAR-BM3D and achieve better speckle noise suppression with stronger adaptability. The experimental results on real SAR images show that the proposed algorithm achieves better comprehensive effect of speckle noise suppression in terms of evaluation indicators and information preservation of SAR images compared with several existing algorithms.

A novel seismic random noise suppression method based on wavelet threshold and Lipschitz

The seismic random noise suppression is very important in the processing and interpretation of seismic data. Wavelet transform is an effective tool to remove random noise. Aiming at the problems of signal propagation point omission and misselection, insignificant denoising effect and poor stability of the traditional wavelet maximum mode (WMM) method, this paper proposes an improved wavelet mode maximum value (IMWMM) denoising method. The Lipschitz of wavelet transform with signal and noise has different features used to distinguish signal and noise. Comparing the propagation points of adjacent scales and removing the points with reduced mode values achieve the separation of seismic signal and noise. The synthetic data, Stanford Earthquake Dataset (STEAD) data and real-field seismic signal experimental results prove the validity of the IMWMM method for both suppressing random noise and preserving seismic signal. The real-field seismic data came from Wenchuan experimental results present that the proposed IMWMM method has effectiveness of random noise suppression with SNR above 28.4527 dB, that has improvement for quality of seismic data.

A Two-Phase Multi-Bit Incremental ADC With Variable Loop Order

This brief presents a two-phase multi-bit incremental analog-to-digital converter (IADC) with variable loop order. In the 1st phase, the loop filter works as a 1st-order topology. In the 2nd phase, the loop reconfigures to a 3rd-order structure, aiming to get the signal-to-quantization-noise ratio (SQNR) boosted quickly within a few clock cycles. Such a two-phase scheme with variable loop-order combines the features of the KT/C noise suppression and high effectiveness of data weighting averaging (DWA) presented by the 1st-order IADC and fast accumulation obtained from the high-order mode. Thereby, with little additional circuitry effort, the proposed IADC improves DWA effectiveness while mitigating the thermal noise penalty when compared with a pure high-order IADC. The proposed architecture is analytically analyzed and exemplarily simulated. Moreover, a design guideline is provided to optimize the allocation of the clock cycles of two phases, thus balancing various significant parameters. Based on the guideline, a circuit-level simulation of an exemplary 1st-to-3rd order IADC was carried out in a 65-nm CMOS process to confirm the results.

Study of dynamic biasing InGaAs/InAlAs avalanche photodiodes with different active areas.

In this work, by comparing and analyzing dynamic biasing InGaAs/InAlAs avalanche photodiodes(APDs) with different active areas, it is found that they have different noise suppression frequency ranges. The upper limit frequency(defined as the frequency at which the noise suppression effect begins to fail) of InGaAs/InAlAs APDs with active area diameter of 50 µm, 100 µm and 200 µm are 2400 MHz, 1990MHz and 1400 MHz respectively. In addition, for InGaAs/InAlAs APDs with an active area diameter of 50 µm, 100 µm and 200 µm, their optimal frequencies of dynamic biasing (defined as the frequency corresponding to the optimal SNR) are 1877MHz, 1670 MHz and 1075 MHz respectively. At last, applying dynamic biasing technology, it achieves a useful gain of 6698.1, which is much greater than that of DC bias (47.2), and this technology has the potential to be applied in high sensitivity laser radar receivers.

A 1/f noise optimized correlated multiple sampling technique for complementary metal oxide semiconductor image sensor

SummaryCorrelated multiple sampling (CMS) technique is often used to reduce random noise in complementary metal oxide semiconductor (CMOS) image sensor, but as the number of samples increases, the suppression of 1/f noise by standard CMS based on averaging sampling gradually decreases. Therefore, in this paper, a 1/f noise optimized correlated multiple sampling (NOCMS) technique based on differentiated sampling weights is proposed. Transfer functions of standard CMS and NOCMS for analyzing the suppression effect of random noise respectively are derived based on the Fourier transform theory. And NOCMS shows a dramatic advantage in the suppression of 1/f noise. In addition, a circuit structure based on single‐slope analog‐to‐digital converter (SSADC) for implementing NOCMS is suggested. Ramp generator provides multiple sets of ramps with different slopes to quantify the reset and signal voltages of pixel output. Sampling weights are increased with the decrease of ramp slopes. The last reset and first signal values are weighted more due to their potentially higher correlations which highlights the principle of assigning weights. Simulation results under 110 nm CMOS technology illustrate that the input‐referred random noise is 142.9 V under standard CMS and 120.9 V under NOCMS when the number of samples equals 8. The noise reduction effect is improved by 15%. NOCMS makes it possible to further reduce 1/f noise of CMOS image sensor.