1,637 research outputs found

    Multi-tone Active Noise Equalizer with Spatially Distributed User-selected Profiles

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    [EN] In this work we propose a multi-channel active noise equalizer (ANE) that can deal with multi-frequency noise signals and assigns simultaneously different equalization gains to each frequency component at each monitoring sensor. For this purpose, we state a pseudo-error noise signal for each sensor of the ANE, which has to be cancelled out in order to get the desired equalization profiles. Firstly the optimal analytic solution for the ANE filters in the case of single-frequency noise is provided, and an adaptive algorithm based on the Least Mean Squared (LMS) is proposed for the same case. We also show that this adaptive strategy reaches the theoretical solution in steady state. Secondly, we state an equivalent approach for the case of multi-frequency noise based on two alternatives: a common pseudo-error signal at each sensor for all frequencies, and a different pseudo-error signal at each sensor for each frequency. The analytic and adaptive solutions for the ANE control filters have been developed for both pseudo-error alternatives. Finally, the ability of the proposed ANE to achieve simultaneously different user-selected noise profiles in different locations has been validated by their transfer functions and simulations.This work was supported by EU jointly with Spanish Government and Generalitat Valenciana under Grants RTI2018-098085-BC41, PID2021-125736OB-I00 (MCIU/AEI/FEDER), RE D2018-102668-T, and PROMETEO/2019/109.Ferrer Contreras, M.; Diego Antón, MD.; Hassani, A.; Moonen, M.; Piñero, G.; Gonzalez, A. (2022). Multi-tone Active Noise Equalizer with Spatially Distributed User-selected Profiles. IEEE/ACM Transactions on Audio Speech and Language Processing. 30:3199-3213. https://doi.org/10.1109/TASLP.2022.3212833319932133

    Adaptive supervisory switching control system design for active noise suppression of duct-like application

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    Active noise suppression for applications where the controlled system response varies with time is a difficult problem, especially for time varying nonlinear systems with large model error. On the basis of adaptive switching supervisory control theory, an adaptive supervisory switching control algorithm is proposed with a new controller switching strategy for active noise suppression of duct-like application. Real time experimental verification tests show that the proposed algorithm is effective with good noise suppression performance

    Cooperative Relaying In Power Line Environment: A Survey and Tutorial

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    Exchange of information is essential in any society and the demand for faster, cheaper, and secure communications is increasing every day. With other hi-tech initiatives like IPv6 and Internet-of-Things (IOT) already in the horizon, demand for broadband is set to escalate beyond its current level. Inherently laden in the challenges posed by this technology are fresh opportunities in terms of penetration of data services into rural communities and development of innovative strategies for more efficient use of the grid. Though still in its developmental phase/stage, Power Line Communication (PLC) has grown beyond theoretical fantasy to become a reality. The proofs are the readily available PLC systems that can be purchased off the shelfto achieve in-house networking and the much talked about, smart metering technology; generally regarded as the “new bride” in utilities industry. One of the biggest gains of PLC is its use of existing electrical cables, thereby eliminating cost of installation and maintenance of data cables. However, given that the power infrastructure was traditionally built to deliver electricity, data signals do suffer various forms of distortions and impairments as they transit it. This paper presents a tutorial on the deployed wireless system technique which is to be adapted to PLC scenario for the purpose of managing the available source energy for achieving reliable communication system. One of these techniques is the cooperative diversity. Its application and deployment in power line environment is explored. The improvement achieved through cooperative diversity in some PLC systems were presented along with the associated limitations. Finally, future areas of research which will further improve the reliability of PLC systems and reduce its power consumption during transmission is shown

    Adaptive Algorithms Design for Active Noise Control Systems with Disturbance at Reference and Error Microphones

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    Active noise control (ANC) is a popular choice for mitigating the acoustic noise in the surrounding environment resulting from industrial and medical equipment, appliances, and consumer electronics. ANC cancels the low frequency acoustic noise by generating a cancelling sound from speakers. The speakers are triggered by noise control filters and produce sound waves with the same amplitude and inverted phase to the original sound. Noise control filters are updated by adaptive algorithms. Successful applications of this technology are available in headsets, earplugs, propeller aircraft, cars and mobile phones. Since multiple applications are running simultaneously, efficiency of the adaptive control algorithms in terms of implementation, computations and performance is critical to the performance of the ANC systems. The focus of the present project is on the development of efficient adaptive algorithms that perform optimally in different configurations of ANC systems suitable for real world applications.Thesis (Ph.D.) -- University of Adelaide, School of Electrical & Electronic Engineering, 202

    Analysis and implementation of active noise control strategies using Piezo and EAP actuators

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    Currently noise cancellation, which affects the lives of people and in the workplace is achieved through the active noise reduction. This measure is not expensive as passive or semi active measures also permits adequate air conduction in duct ventilation systems. The system control is achieved through a suitable location of the phase in the cancelling noise signal relative to the signal primary noise. Algorithms have been developed and strategies for active noise reduction and its implementation and experimental testing on duct ventilation. The actives elements used are Piezo Actuators and EAP as speakers; Individual and collective operation of the aforementioned actuators is examined. The work was evaluated as follows: Analysis of previous research on existing algorithms for active noise reduction. Study the strategies of simulation and implementation for active noise control algorithms designed.Tesi

    Optimal control algorithm design for a prototype of active noise control system

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    High-level noise can represent a serious risk for the health, industrial operations often represent continuous exposure to noise, thus an important trouble to handle. An alternative of solution can be the use of passive mechanisms of noise reductions, nonetheless its application cannot diminish low-frequency noise. Active Noise Control (ANC) is the solution used for low-frequency noise, ANC systems work according to the superposition principle generating a secondary anti-noise signal to reduce both. Nevertheless, the generation of an anti-noise signal with same oppose characteristics of the original noise signal presupposes the utilization of special techniques such as adaptive algorithms. These algorithms involve computational costs. The present research present the optimization of a specific ANC algorithm in the step-size criteria. Delayed Filtered-x LMS (FxLMS) algorithm using an optimal step-size is evaluated in a prototype of ANC system.Tesi

    Active disturbance cancellation in nonlinear dynamical systems using neural networks

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    A proposal for the use of a time delay CMAC neural network for disturbance cancellation in nonlinear dynamical systems is presented. Appropriate modifications to the CMAC training algorithm are derived which allow convergent adaptation for a variety of secondary signal paths. Analytical bounds on the maximum learning gain are presented which guarantee convergence of the algorithm and provide insight into the necessary reduction in learning gain as a function of the system parameters. Effectiveness of the algorithm is evaluated through mathematical analysis, simulation studies, and experimental application of the technique on an acoustic duct laboratory model
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