Noise Attenuation Levels Research Articles

An Experimental Method for Bio-Signal Denoising Using Unconventional Sensors.

In bio-signal denoising, current methods reported in the literature consider purely simulated environments, requiring high computational powers and signal processing algorithms that may introduce signal distortion. To achieve an efficient noise reduction, such methods require previous knowledge of the noise signals or to have certain periodicity and stability, making the noise estimation difficult to predict. In this paper, we solve these challenges through the development of an experimental method applied to bio-signal denoising using a combined approach. This is based on the implementation of unconventional electric field sensors used for creating a noise replica required to obtain the ideal Wiener filter transfer function and achieve further noise reduction. This work aims to investigate the suitability of the proposed approach for real-time noise reduction affecting bio-signal recordings. The experimental evaluation presented here considers two scenarios: (a) human bio-signals trials including electrocardiogram, electromyogram and electrooculogram; and (b) bio-signal recordings from the MIT-MIH arrhythmia database. The performance of the proposed method is evaluated using qualitative criteria (i.e., power spectral density) and quantitative criteria (i.e., signal-to-noise ratio and mean square error) followed by a comparison between the proposed methodology and state of the art denoising methods. The results indicate that the combined approach proposed in this paper can be used for noise reduction in electrocardiogram, electromyogram and electrooculogram signals, achieving noise attenuation levels of 26.4 dB, 21.2 dB and 40.8 dB, respectively.

The Importance of Noise Attenuation Levels in Neonatal Incubators

Background: It is known that high noise levels can be harmful to preterm infants, causing physiological and psychological disorders. It is also known that premature babies spend a lot of time in an incubator. In this sense, many studies show that incubator noise levels can range from 45 to 70 dB. However, these differences in noise levels depend, fundamentally, on the wide range of methodology that can be used. This study aims to know the levels of noise from a fan in the incubator itself and how much it can isolate the noises coming from the outside. Methods: For this purpose, the noise levels of three incubators were measured within a sound-dampened booth for free-field audiometry. For the emission of acoustic energy, a pink noise generator was used; likewise, two microphones were placed, one inside the incubator cabin and the other outside, to determine the acoustic insulation levels of the tested incubators. Results: The incubators produced equivalent continuous sound pressure levels between 53.5 and 58 dB. Acoustic insulation analysis showed that levels varied from one incubator to another, between 5.2 and 10.4 dB. Conclusions: It is necessary to improve the acoustic insulation inside the incubator cabin and to reduce the noise levels of the motor fan. On the other hand, although the incubators are meeting the noise criteria set out in the IEC60601-2-19: 2009 standard of 60 dBA, under normal use conditions, they are still far from the limit recommended by the American Academy of Pediatrics (45 dBA).

An extrapolation-based virtual sensing technique of improving the control performance of the FxLMS algorithm in a maritime environment

Several local active noise control (ANC) approaches based on Filtered-x Least Mean Square (FxLMS) algorithm have been designed to mitigate low frequency noise annoyance from undesirable acoustic sources, for which conventional passive techniques are ineffective. A fundamental limitation of local ANC is the small size of quiet zone that is extended around the error microphone. This means that the physical sensor should be mounted at the desired location of noise attenuation, which in most cases is practically inconvenient. In order to extend the zone of quiet close to the ears of a seated passenger who moves gently his head, a number of complicated and computationally heavy virtual sensing algorithms have been developed for ANC. The spatial performance of such a local active sound controller depends not only on the correlation properties of the primary sound field and the adaptation algorithm but also on the microphones spatial arrangement, the size and the number of the control sources. Thus, the objective of this work is to develop a simple, robust and computationally-efficient virtual sensing ANC algorithm of improving the performance of the conventional FxLMS. The main approach to do so is by using a feedforward ANC controller based on the combined solution of first-order pressure prediction technique and a mixed-error design integrating the FXLMS algorithm for enhancing the noise attenuation levels and shaping an extended silence zone. Aim of this work is also to estimate a simplified approach of the virtual secondary path in order to be more challenging in practical and commercial applications, while the ANC system can achieve adequate control performance.In an effort to test the extension degree of the silence zone generated at a fixed virtual location, low computational demand ANC headrest configurations, are investigated. The proposed schemes have been tested through a simulation model, a test rig and an experimental ANC system installed in a cabin mock-up. The computer-modeled and the experimental results demonstrate that the proposed local virtual sensing ANC algorithm maintains stability in all operating points, and works reliably and more effectively than the widely used conventional FxLMS algorithm.

Parallel feedback active noise control of MRI acoustic noise with signal decomposition using hybrid RLS-NLMS adaptive algorithms.

This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27 dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.

A two-channel feedback active noise control system with delayless subband architecture to reduce compressor noise of an enclosed heating, ventilation and air conditioning unit

This paper discusses the development of an active noise control (ANC) system to cancel compressor noise produced by a commercially available heating, ventilation and air conditioning unit enclosed within a closet. Feedback ANC architecture that requires no reference microphone is used for cost-effectiveness. A novel delayless subband adaptive filtering technique is used to reduce computational complexity of the algorithm and improve system performance. Finally, the system is extended to two-channel architecture in order to provide an additional zone of silence. Using an experimental setup, the noise from the compressor at two error microphone positions is recorded and all necessary secondary path measurements are taken. Noise attenuation levels of 11 dB and 21 dB are obtained at the two error microphones, resulting in an average attenuation of 18 dB.

Performance of a dual-cup-dual-cushion earmuff design

Traditionally, earmuffs have been constructed consisting of a single-walled cup seated on a flexible ear cushion, forming a �single-cup-single-cushion� (SCSC) structure. The average noise attenuation levels provided by SCSC earmuffs typically range from 15 dB at low frequencies to 40 dB at high frequencies. It is difficult to further improve the attenuation of SCSC earmuffs beyond this level in practice unless the structural design is modified radically. One candidate design that is substantially different from the SCSC structure is a �dual-cup-dual-cushion� (DCDC) structure, where the earmuff consists of two independent earcup shells that are resiliently coupled together. This DCDC structure is based on a concept originally introduced by Shaw and Thiessen in an earlier study [J. Acoust. Soc. Am. 34, 1233�1246]. The present study further explores the dynamic characteristics of the DCDC design by extending the theoretical investigation to higher frequencies using a finite element model, which complements the classical lumped parameter model for low frequency analysis. Furthermore, a laboratory DCDC earmuff prototype is constructed and compared experimentally to a commercial SCSC earmuff. The attenuation data obtained from the acoustic test fixture test indicate significant performance improvement of the DCDC earmuff over the SCSC earmuff. The Real-Ear-Attenuation-at-Threshold test results show attenuation gains ranging from several dB at 125 Hz, up to 10 dB at 250, 500 and 1000 Hz, and slightly more than 10 dB above 2000 Hz.

Noise attenuation performance of deep-insert custom earplugs under single and double hearing protection

This paper evaluates various aspects of noise attenuation performance of deep-insert custom earplugs (DICEPs). Different from traditional custom earplugs, the DICEPs refer to solid earplugs that are custom-manufactured from ear impressions and fit deeply into earcanals of individual users, reaching or passing the second bend of the earcanal. The DICEP was recently developed to provide more reliable hearing protection performance for personnel working in extremely hazardous noise environments. In this paper, a review of prior literature regarding hearing protector performance was given to illustrate the need for performance evaluation on laboratory and field attenuation of DICEP devices. Real-Ear Attenuation at Threshold (REAT) measurements were used to evaluate noise attenuation levels of the DICEP when used alone as single hearing protection (SHP), and in combination with a circumaural earmuff as double hearing protection (DHP). It was experimentally determined that the mean attenuation levels of the DICEP SHP and DICEP DHP systems ranged from 37 to 45 dB and 38 to 48 dB across one-third octave bands spanning from 125 Hz to 8 kHz with NRRs of 29 dB and 32 dB, respectively. Furthermore, the performance consistency for multiple insertions and stability against kinetic activities after the initial insertion of the DICEP SHP and DHP systems were also investigated. Statistical analyses of the test data showed that the DICEP noise attenuation performance was consistent in both SHP and DHP configurations, despite variations in user experience level, fitting protocol and fitting iteration. In addition, the DICEP performance was also observed to be highly stable against jaw and whole-body activities that may be required by users during continuous use in the field.

ℋ︁∞ and l2–l∞ filtering for two‐dimensional linear parameter‐varying systems

AbstractIn this paper, the ℋ︁∞ and l2–l∞ filtering problem is investigated for two‐dimensional (2‐D) discrete‐time linear parameter‐varying (LPV) systems. Based on the well‐known Fornasini–Marchesini local state‐space (FMLSS) model, the mathematical model of 2‐D systems under consideration is established by incorporating the parameter‐varying phenomenon. The purpose of the problem addressed is to design full‐order ℋ︁∞ and l2–l∞ filters such that the filtering error dynamics is asymptotic stable and the prescribed noise attenuation levels in ℋ︁∞ and l2–l∞ senses can be achieved, respectively. Sufficient conditions are derived for existence of such filters in terms of parameterized linear matrix inequalities (PLMIs), and the corresponding filter synthesis problem is then transformed into a convex optimization problem that can be efficiently solved by using standard software packages. A simulation example is exploited to demonstrate the usefulness and effectiveness of the proposed design method. Copyright © 2007 John Wiley & Sons, Ltd.

An overview of flow control for fan noise reduction

The dominant tonal noise source from modern high-bypass-ratio turbofan aircraft engines is due to the impingement of viscous fan rotor wakes onto the downstream stator row. Prior research conducted at NASA Glenn Research Center’s Active Noise Control Fan (ANCF) rig has demonstrated that significant tonal noise attenuation can be achieved by injecting 1.2% to 1.8% of the fan throughflow along a slot in the trailing edge of the rotor. Efforts presented in this paper have focused on reducing the required blowing mass flow while maintaining equivalent noise attenuation levels. Two primary approaches were investigated: blowing in circumferentially non-uniform patterns (i.e., blowing on every other blade), and optimizing the injection scheme itself. The concept of blowing on alternate rotors was experimentally tested in the ANCF rig using NASA’s current slot-blown rotors, and improved attenuation efficiencies were found (although the overall attenuation levels were less). Cascade wind tunnel tests of several different injection schemes were conducted, and the best-performing configuration was incorporated into a new rotor design for experimental validation in the ANCF rig. These rotors achieved similar tonal noise attenuation levels as the slot-blown configuration, but they required injecting less than 0.75% of the fan throughflow.

A low-cost digital signal processor-based ear-muff with adaptive active noise control

This paper presents the design and implementation of a digital signal processor (DSP)-based feed-forward narrow-band noise canceling system using the Analog Devices ADSP-2181 EZ-KIT Lite developer's kit. The theory of adaptive noise control (ANC) is applied to an ear-muff so that the entire system combines both passive and active techniques to reduce the harmful acoustic noise emitted by machinery and engines. The ANC developed uses a 100-tap finite impulse response (FIR) filter which encompasses the least mean square (LMS) and normalised LMS (NLMS) algorithms to adaptively `track' changing input conditions. The hardware and software aspects for real-time implementation, the signal conditioning circuits and the software developed for stereo multiplexing in the EZ-KIT Lite environment are presented. Performance results show significant improvements in noise attenuation levels when compared to use of a purely passive technique.