Noise Suppression Techniques Research Articles

Prediction of Thin Shoal Reservoirs Under Reef Controlled by Isochronous Stratigraphic Framework

Despite the great success in the global exploration and development of reef reservoirs, research on bioclastic shoals under reefs is still in its infancy. Bioclastic shoal reservoirs are very thin, with multiple vertical levels and fast lateral changes, which makes accurate prediction of the reservoir’s location much tougher. To further implement the reservoir distribution, under the guidance of sequence stratigraphy, the prediction of thin shoals under the control of an isochronous stratigraphic framework was established. Using the combination of spectrum shaping and F-X domain noise suppression techniques and utilizing the signal-to-noise ratio spectrum set as the reference, logging curve as supervision, and well seismic calibration and isochronal amplitude slicing as quality control, the seismic frequency band was extended, and the seismic data resolution and signal-to-noise ratio were improved. After frequency extension, the global optimal seismic automatic interpretation technique was used to construct an isochronal stratigraphic framework model. Through waveform facies-controlled inversion and waveform facies-controlled simulation techniques, the elastic properties of the shoal reservoir were obtained, from which the planar distribution of the reservoir was accurately predicted. The above methods were applied to the prediction of the bioclastic shoal reservoir in the lower submember of the Changxing formation in the Yuanba gas field (China). The plane distribution of bioclastic shoal in the first and second levels was identified, which provides a guideline for the prediction of thin shoal reservoirs.

Integrated noise suppression techniques for enhancing voice activity detection in degraded environments

Integrated noise suppression techniques for enhancing voice activity detection in degraded environments

Electromagnetic noise characteristics analysis and noise traceability in induction motor

Abstract To investigate the electromagnetic vibration and noise issues in induction motors, this study employs a combined methodology of experimental, theoretical, and simulation approaches to analyze the characteristics of electromagnetic noise. Initially, a theoretical analysis of the radial electromagnetic force of the motor is conducted, followed by a simulation of the motor’s electromagnetic vibration and noise at a working condition of 3000 rpm, incorporating a Multiphysics coupled analysis of electromagnetic-vibration-noise. Vibration testing on a specific compressor motor reveals that the primary vibration noise characteristic frequency is centered around 2000 Hz. A comparison between simulation and experimental results shows a high degree of congruence, indicating the reliability of the simulation method. Subsequently, an acoustic camera kit, Brüel & Kjær PULSE Reflex, based on a beamforming method, is employed for noise source identification and acoustic holography testing at 3000 rpm, which successfully localizes the noise sources. The analysis and experiments provided herein can serve as a reference for the development of electromagnetic vibration noise suppression techniques in induction motors.

Adaptive Filtering Noise Suppression Technique for EFA-Based Interferometric Fiber Optic Sensors

Adaptive Filtering Noise Suppression Technique for EFA-Based Interferometric Fiber Optic Sensors

Research on the Innovation and Development of Gravitational Wave Detection Technology

According to Einstein’s general theory of relativity, gravity is described as the curvature of space-time caused by gravitational sources, and to prove the existence of gravitational waves, many scientific research institutes around the world have begun to build equipment to try to detect gravitational waves in the vast background signals of the universe. At present, gravitational waves have been detected by many scientific research institutions and scientists. Now, the detection of gravitational waves has shifted to the direction of high precision and accuracy. This paper starts with the laser interferometer, the most basic instrument for gravitational wave detection. It expounds on the latest development progress and key technologies of gravitational wave detection in the current physical world, including noise suppression and gravitational wave detection spacecraft projects. In terms of laser interferometers, this paper describes their principle and key technologies and puts forward the difficult problems that still need to be tackled and studied. In terms of noise suppression, this paper describes the noise and interference that may be generated and how to suppress the noise to avoid interfering with the accuracy of the experiment. It also points out the shortcomings of current noise suppression techniques. For gravitational wave detection spacecraft projects, this paper first focuses on several key projects in the world, then describes the technologies and shortcomings of spacecraft, and puts forward the direction of improvement and in-depth research on these technologies. This paper aims to summarize the key technologies of gravitational wave detection in the world today and point out the direction of its future development.

Phase noise suppression technique based on an improved reference interferometer scheme.

The reference interferometer scheme is an effective noise reduction method, but the optical path length difference (OPD) of the two interferometers must be strictly equal, which limits its application in practical environments. In this paper, an improved reference interferometer demodulation technique without strictly equal OPDs is proposed to suppress phase noise. By introducing a reference interferometer, the phase noise can be removed from the demodulation results. The combination of the differential self-multiplication algorithm and the fitted phase modulation depth calculation formula can evaluate the phase modulation depth of both interferometers in real time and simultaneously eliminate the nonlinear distortion caused by phase modulation depth drift and the effect of different OPDs on the reference interferometer scheme. The experimental results show that the technique can obtain highly stable and accurate demodulation results even if the OPDs of the two reference interferometers are different. The phase modulation depth calculation error is less than 0.57%, the maximum phase noise reduction is 15 dB, the average reduction is 9 dB, the minimum total harmonic distortion is 0.17%, and the SINAD reaches 35.90 dB.

An adaptive optimum weighted mean filter and bilateral filter for noise removal in cardiac MRI images

Medical diagnosis greatly benefits from the use of MRI images. There have been many MRI image enhancement algorithms proposed over the years to aid doctors in disease diagnosis. Conventional image enhancing methods, nevertheless, may also boost the noise that was already there in the captured picture, which might cause distortion, which is unfavourable for the disease diagnosis. Therefore, an appropriate technique for noise suppression is necessary. An attempt has been made to incorporate a two-step filtering based algorithm for noise removal in cardiac MRI images while maintaining the images crucial compositional elements, such as their borders and textures. A combination of adaptive optimum weighted mean filter (AOWMF) and bilateral filter (BF) has been implemented to reduce impulsive noise and Gaussian noise that are both present as mixed noise. The fundamental idea of the AOWMF approach includes the detection of noise pixels using Crow Optimization Algorithm (COA), and replacing them with an optimum weighted mean value depending on a criterion of maximization fitness function. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) have been used to assess the effectiveness of the employed noise reduction technique. The result analysis are experimented in MATLB which reveals that proposed method is able to achieve high PSNR and SSIM and further, this method has the potential to enhance more detail structures of the input cardiac MRI images than existing methods.

Using geometric mode decomposition for the background noise suppression on microseismic data

AbstractMicroseismic datasets typically have relatively low signal‐to‐noise ratio waveforms. To that end, several noise suppression techniques are often applied to improve the signal‐to‐noise ratio of the recorded waveforms. We apply a linear geometric mode decomposition approach to microseismic datasets for background noise suppression. The geometric mode decomposition method optimizes linear patterns within amplitude–frequency modulated modes and can efficiently distinguish microseismic events (signal) from the background noise. This method can also split linear and non‐linear dispersive seismic events into linear modes. The segmented events in different modes can then be added carefully to reconstruct the denoised signal. The application of geometric mode decomposition is well suited for microseismic acquisitions with smaller receiver spacing, where the signal may exhibit either (nearly) linear or non‐linear recording patterns, depending on the source location relative to the receiver array. Using synthetic and real microseismic data examples from limited‐aperture downhole recordings only, we show that geometric mode decomposition is robust in suppressing the background noise from the recorded waveforms. We also compare the filtering results from geometric mode decomposition with those obtained from FX‐Decon and one‐dimensional variational mode decomposition methods. For the examples used, geometric mode decomposition outperforms both FX‐Decon and one‐dimensional variational mode decomposition in background noise suppression.

Generation of high-speed PAM-4 signal with 3-bit DAC enabled by CRD-NS in optical interconnect.

In this paper, we experimentally demonstrated a 2-km high-speed optical interconnection with pulse-shaped pre-equalized four-level pulse amplitude modulation (PAM-4) signal generated by a 3-bit digital-to-analog converter (DAC) with the aid of in-band quantization noise suppression techniques under different oversampling ratios (OSRs) to reduce the influence of quantization noise. The simulation results show that the quantization noise suppression capability of high computational complexity digital resolution enhancer (DRE) is sensitive to taps number of the estimated channel and match filter (MF) response when OSR is sufficient, which will lead to further significant computational complexity increase. To better accommodate this issue, channel response-dependent noise shaping (CRD-NS) which also takes channel response into consideration when optimizing quantization noise distribution is proposed to suppress the in-band quantization noise instead of DRE. Experimental results show that about 2 dB receiver sensitivity improvement can be achieved at the hard-decision forward error correction (HD-FEC) threshold for 110 Gb/s pre-equalized PAM-4 signal generated by 3-bit DAC when the traditional NS technique is replaced by the CRD-NS technique. Compared to the high computational complexity DRE technique, in which channel response is also considered, negligible receiver sensitivity penalty is observed for 110 Gb/s PAM-4 signal, when the CRD-NS technique is utilized. Considering both the system cost and bit error ratio (BER) performance, the generation of high-speed PAM signal with 3-bit DAC enabled by the CRD-NS technique is regarded as a promising scheme for optical interconnection.

An Adaptive Spectral Subtraction Algorithm to Remove Persistent Cultural Noise

ABSTRACT Seismic stations and seismic arrays suffer from unwanted seismic noise as a result of inevitable population growth and development. This encroachment of noise degrades stations’ performance. Moving stations to a quieter location breaks the continuity of historical records and can be logistically complicated. This is especially true for seismic arrays that requires a larger footprint. In this study, we examine the feasibility and merit of an adaptive denoising algorithm to reduce the impact of persistent anthropogenic noise. We build our algorithm on spectral subtraction techniques that have been commonly applied to speech and audio traces and develop a noise-suppression technique that is tailored for seismic data. Using the continuous wavelet transform, we subtract estimates of the noise in the frequency domain. We evaluate this algorithm on synthetic data, consisting of a set of carefully selected events on a low-noise array environment in Alaska. Then we apply this technique to a seismic array in Turkey known to suffer from persistent anthropogenic noise. Our results on individual seismic traces demonstrate that the noise-suppression technique is quite successful at improving the signal-to-noise ratio of key seismic phases. The strengths of this approach include its intuitiveness, its ability to adapt to changes in the background noise, and the ability to reduce noise while preserving the phase of the original signal—a prerequisite for use in array analysis. When the denoised traces are used for array analysis we do not find the noise suppression to be as effective as it is on individual traces. We explore a number of reasons why this performance is less than desired. Despite the results of our particular implementation, we demonstrate that the larger family of spectral subtraction techniques offer considerable adaptability and deserve more attention in the seismic community.

Cooling of an integrated Brillouin laser below the thermal limit.

Photonically integrated resonators are promising as a platform for enabling ultranarrow linewidth lasers in a compact form factor. Owing to their small size, these integrated resonators suffer from thermal noise that limits the frequency stability of the optical mode to ∼100 kHz. Here, we demonstrate an integrated stimulated Brillouin scattering (SBS) laser based on a large mode-volume annulus resonator that realizes an ultranarrow thermal-noise-limited linewidth of 270 Hz. In practice, yet narrower linewidths are required before integrated lasers can be truly useful for applications such as optical atomic clocks, quantum computing, gravitational wave detection, and precision spectroscopy. To this end, we employ a thermorefractive noise suppression technique utilizing an auxiliary laser to reduce our SBS laser linewidth to 70 Hz. This demonstration showcases the possibility of stabilizing the thermal motion of even the narrowest linewidth chip lasers to below 100 Hz, thereby opening the door to making integrated microresonators practical for the most demanding future scientific endeavors.

Passive suppression of radiation of low-frequency underwater noise

Using an exact solution of the problem of spherical wave diffraction on a fluid sphere, it has been predicted [Godin and Baynes, J. Acoust. Soc. Am. 143, EL67–EL73 (2018)] that passive, broadband suppression of radiation of low-frequency sound can be achieved by placing an acoustically compliant object in the vicinity of the source. In underwater acoustics, the compliant object can be realized as an air-filled bladder. One of the promising applications of the technique is to suppress the noise generated by ship propellers. If implemented on a wide scale, the passive noise suppression technique would help to decrease the noise levels due to commercial and recreational vessels and reduce the detrimental effects of anthropogenic noise on marine life. This paper extends the earlier theoretical treatment of the problem to more realistic models of the compliant object such as a gas volume surrounded by a stretchable membrane (a balloon) and a thin shell. The effect of the finite depths of low-frequency noise source and the compliant object on noise levels in the far field will be discussed.

Application of aerating techniques for noise suppression in capillary tubes

A method for suppressing noise in capillary tubes was developed with aerating techniques. The refrigerant R600a was added to the outlet of a throttling capillary from the end of a transition tube between the capillary and evaporator. To investigate the flow characteristic of R600a in the transition tube, a two-phase flow quasi-steady simulation was performed using the mixture model. The Schnerr–Sauer cavitation model was used, and the turbulence model was realizable k − ɛ. Numerical results show that the local pressure and negative mass transfer rate can both be reduced at the downstream of the capillary where bubbles collapse, when bypass capillaries are used in the aerating model. An experimental system was built to measure the noise in a transition tube with/without a bypass capillary. Results show that the noise sound pressure level decreased by 2 dB on average when aerating techniques were used. This research describes the complex mechanism of the throttling flashing process and provides an effective method to suppress the noise in capillary tubes, which will be beneficial to improve occasional sharp noise in a household refrigerator.

Speckle Noise Suppression Algorithm of Holographic Display Based on Spatial Light Modulator

Holography has emerged as one of the most attractive three-dimensional display technologies. With the technological development of computer science and coherent light source, the computer-generated holography has been applied in many fields. However, the speckle noise of the holographic reconstructed image seriously affects the viewing experience. In this paper, the cause of speckle noise generation in holographic display is introduced. Then, discussions about the speckle noise suppression methods are provided. The discussions are categorized into iterative and non-iterative approaches. Besides, we also introduce other speckle noise suppression techniques which are proposed from the perspective of light coherence, human visual system and optical system. Finally, the prospects of different types of approaches are summarized.

Automated Event Detection and Denoising Method for Passive Seismic Data Using Residual Deep Convolutional Neural Networks

There has been a recent rise in the uses and applications of passive seismic data, such as tomographic imaging, volcanic monitoring, and hydrocarbon exploration. Consequently, the sharp increase in passive seismic applications requires real-time event detection capabilities with high accuracy. Proper analysis of such events depends largely on the signal-to-noise ratio improvement through noise suppression techniques. Recent advances in the fields of signal processing and deep learning coupled with the available computational resources provide a great opportunity to address this challenge. In this work, a workflow is proposed where a residual deep neural network is customized and employed to detect passive seismic events. The automated detection is followed by a denoising step to extract the signal of interest from background noise using an IIR Wiener filter. The proposed method does not require any prior knowledge of the signal/noise, and therefore, it can work with various types of signals/noises. Another benefit of the proposed detection method is that the deep neural network is trained only on synthetic seismic data without the need to use real data in the training process. Nevertheless, it exhibits high accuracy in detecting and denoising events from real passive seismic data sets. In particular, field seismic data is recorded in northern Saudi Arabia and used to test the complete detection and denoising method. The detection method proved its capability of detecting events automatically in large data sets and in real time (due to off-line training).

Seismic Random Noise Attenuation via Self-Supervised Transfer Learning

Random noise attenuation is an important step in seismic data processing. Unfortunately, most conventional denoising methods heavily rely on specific prior knowledge and fine-tuning of the parameters. Therefore, they often fail to suppress random noise. Recent works based on supervised learning techniques for seismic noise suppression show outstanding performance. However, this paradigm needs large-scale labeled training datasets that are not available for seismic field data. Inspired by the self-supervised learning, we propose a promising unsupervised learning scheme that aims at suppressing the random noise with only a noisy shot gather. The method is based on a specific <inline-formula> <tex-math notation="LaTeX">$\mathcal {J}$ </tex-math></inline-formula>-invariant function and an assumption that the noise is statistical independent while the useful signal exhibits some correlation. To further improve the denoising quality, we integrate the transfer learning strategy. We experimentally demonstrate that the proposed framework faithfully recovers the denoised data on both prestack and poststack synthetic and field data although the pretrained network is trained with the prestack synthetic dataset. The preliminary comparisons with traditional and learning-based approaches indicate the effectiveness and robustness as well.

Implementation of Modified Wiener Filtering in Frequency Domain in Speech Enhancement

The most common complaint about Digital Hearing Aids is feedback noise. Many attempts have been undertaken in recent years to successfully reduce feedback noise. A wiener filter, which calculates the wiener gain using before and after filtering SNR, is one technique to reduce background noise. Modified Noise Reduction Method (MNRM), a new way for reducing feedback noise Reduction, is presented in this work. In the Modified Noise Reduction Strategy, the advantages of a wiener filter are merged with a decision-directed approach and a twin-stage noise suppression technique The Modified Noise Reduction method can reduce the noise more successfully, according to comprehensive MATLAB programming, investigation, and findings analysis. After being modelled in MATLAB for seven distinct noise types, the SNR of the two architectures is compared.

An integrated 0.0625–4 GHz quadrature-output fractional-N frequency synthesizer for software-defined radios

This paper presents a compact 0.0625–4 GHz fractional-N frequency synthesizer with quadrature phase output for software-defined radios (SDRs). Four voltage controlled oscillators (VCOs) and six cascaded dividers are used for wideband operation. Second harmonic filtering and high frequency noise suppression techniques are applied in VCO for phase noise optimization. Inverter switch and cascade switch buffers are combined for channel selection enhancement and output amplitude improvement. A large output voltage dynamic range with minimum current variation and mismatch is achieved by enabling transistors to work in triode region in charge pump. Implemented in a 55 nm CMOS process, the synthesizer demonstrates continuous frequency coverage from 62.5 to 4000 MHz with orthogonal output signals greater than 2 dBm while consuming 125 mW of power and provides the phase noise performance of −96.3/-127.7 dBc/Hz at 10 kHz/1 MHz offsets under a 2 GHz carrier. The chip area including all the pads and IOs is 3.34 mm2.

Adaptive Phase Noise Cancellation Technique for Fiber-Optic Interferometric Sensors

The optical source phase noise is one of the main factors influencing the noise performance of fiber-optic interferometric measurement systems. The phase noise is directly proportional to the optical path length difference of the interferometer and wavelength instability of the optical source. Conventional phase noise suppression techniques involve the use of highly stable optical sources and reduction of path length differences of sensing interferometers. However, such methods are not always appropriate for all interferometric configurations. Alternative phase noise suppression techniques suggest the use of an auxiliary reference interferometer for independent measurements of the phase noise. In this case, the phase noise signal can be directly subtracted from the sensor signal. But equal path length differences are required for all interferometers in the measurement system. In this paper, an adaptive phase noise cancellation technique for fiber-optic interferometric sensors is presented. The proposed technique is based on the real-time evaluation of optical path length differences for all interferometers in the measurement system. This approach doesn't require identical path length differences and takes into account their variations caused by environmental conditions. Thus, the optical source phase noise can be independently measured by the reference interferometer and subtracted from the sensor signal with the required attenuation. The results of experimental investigations of the proposed technique for two types of interferometric schemes are presented. It is shown that the proposed technique demonstrates the phase noise reduction up to 30 dB in the frequency range up to 500 Hz.

An effective and universal intensity noise suppression technique for single-frequency fiber lasers at 1.5 μm

We report on an effective and universal technique to fulfill intensity noise suppression for single-frequency fiber lasers (SFFLs) at 1.5 μm. Utilizing a gain-saturated semiconductor optical amplifier and the effective filtering of amplified spontaneous emission, the resultant relative intensity noises of three diverse SFFLs are maintained at −155 dB Hz−1; which is only <0.9 dB from the shot noise limit in the frequency range from 100 kHz to 50 MHz. Refering to the three paradigmatic experimental results, this technology, as a promising external solution of noise suppression, can be modularized to promote the application of SFFLs.