2,460 research outputs found

    Active noise control for motors in operating range from 200 TO 3000 RPM and noise levels around 90 dBA

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    La continua exposiciรณn al ruido es un mal que podrรญa generar un efecto adverso para la salud. Sin embargo, es considerado como un efecto inherente a los procesos industriales, incluso propio de รกreas comerciales en las que es difรญcil fiscalizar debido al alto trรกnsito y congestiรณn vehicular. No obstante, en muchos casos se ha tratado de reducir sus efectos utilizando mecanismos pasivos como el uso de materiales absorbentes, los cuales, a pesar de ser efectivos en algunos casos, pueden resultar insuficientes para cancelar ruido a bajas frecuencias. Por otro lado, puede ser imprรกctico para zonas en las que el espacio es limitado. En busca de resolver estas desventajas, mecanismos de control activo, en los que es necesario tener fuentes secundarias de sonido, se han desarrollado para la cancelaciรณn del ruido mediante interferencia destructiva. Debido a que una segunda fuente de sonido es necesaria, dicha fuente necesitarรก controlarse mediante un algoritmo que pueda obtener la superposiciรณn deseada. En el presente trabajo, algoritmos de control activo de ruido son analizados, simulados e implementados. Asรญ mismo, se presenta al algoritmo Least-Mean-Square como el mรกs conveniente en control de ruido. Finalmente, motores elรฉctricos y de combustiรณn interna dentro del rango de 200 a 3000 RPM (revoluciones por minuto), los cuales generan alrededor de 90 dB de ruido, son evaluados.Continuous exposure to noise can generate a detrimental effect in health. However, it is considered as an inherent issue on industrial processes or even on commercial areas where heavy traffic and congestion are difficult to supervise. Hence, it has been tried to be reduced through passive mechanism, such as absorbing materials, which result to be ineffective cancelling low frequencies. Additionally, it could be unpractical when there are space limitations. In order to overcome these drawbacks, active control approaches have been developed in which a secondary sources array is required to cancel the main source by destructive interference. Due to the fact that a secondary source is expected to be equal in amplitude and opposite in phase, secondary sources need a particular control algorithm to achieve the desired superposition. In this work active noise control strategies are analysed, simulated and implemented. Furthermore, adaptive algorithm Least-Mean-Square is presented as the most convenient classic control strategies. For this purpose, Diesel and Electric motors under operating range from 200 to 3000 RPM (revolution per minute) are evaluated considering noise levels around 90 dB

    Power System Harmonics Estimation Using Adaptive Filters

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    Accurate estimation and tracking of power quality disturbances requires efficient adaptive model based techniques which should have elegant structures to be implemented in practical systems. Adaptive filters have been used as a popular estimator to track the time-varying power quality events, but the performance is limited due to higher order nonlinearity exists in system dynamics. Harmonics generated in the generation and distribution system are one of the critical power quality issues to be addressed properly. Least mean square (LMS) and recursive least square (RLS) based adaptive estimation models can be used to track the harmonic amplitudes and phases in practical power system applications. Due to time varying nature of harmonic parameters, modifications have to be incorporated in adaptive filters based modeling during estimation of the harmonic parameters and decaying DC components present in the distorted power signals. Volterra expansions can be combined with the adaptive filtering to improve the estimation accuracy and enhance the convergence rate of the estimation model

    LMS Adaptive Filters for Noise Cancellation: A Review

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    This paper reviews the past and the recent research on Adaptive Filter algorithms based on adaptive noise cancellation systems. In many applications of noise cancellation, the change in signal characteristics could be quite fast which requires the utilization of adaptive algorithms that converge rapidly. Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation. The purpose of this paper is not only to discuss various noise cancellation LMS algorithms but also to provide the reader with an overview of the research conducted

    Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

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    The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

    ์˜คํ”„์…‹ ์ œ๊ฑฐ๊ธฐ์˜ ์ ์‘ ์ œ์–ด ๋“ฑํ™”๊ธฐ์™€ ๋ณด์šฐ-๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋ฅผ ํ™œ์šฉํ•œ ์ˆ˜์‹ ๊ธฐ ์„ค๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021.8. ์—ผ์ œ์™„.In this thesis, designs of high-speed, low-power wireline receivers (RX) are explained. To be specific, the circuit techniques of DC offset cancellation, merged-summer DFE, stochastic Baud-rate CDR, and the phase detector (PD) for multi-level signal are proposed. At first, an RX with adaptive offset cancellation (AOC) and merged summer decision-feedback equalizer (DFE) is proposed. The proposed AOC engine removes the random DC offset of the data path by examining the random data stream's sampled data and edge outputs. In addition, the proposed RX incorporates a shared-summer DFE in a half-rate structure to reduce power dissipation and hardware complexity of the adaptive equalizer. A prototype chip fabricated in 40 nm CMOS technology occupies an active area of 0.083 mm2. Thanks to the AOC engine, the proposed RX achieves the BER of less than 10-12 in a wide range of data rates: 1.62-10 Gb/s. The proposed RX consumes 18.6 mW at 10 Gb/s over a channel with a 27 dB loss at 5 GHz, exhibiting a figure-of-merit of 0.068 pJ/b/dB. Secondly, a 40 nm CMOS RX with Baud-rate phase-detector (BRPD) is proposed. The RX includes two PDs: the BRPD employing the stochastic technique and the BRPD suitable for multi-level signals. Thanks to the Baud-rate CDRโ€™s advantage, by not using an edge-sampling clock, the proposed CDR can reduce the power consumption by lowering the hardware complexity. Besides, the proposed stochastic phase detector (SPD) tracks an optimal phase-locking point that maximizes the vertical eye opening. Furthermore, despite residual inter-symbol interference, proposed BRPD for multi-level signal secures vertical eye margin, which is especially vulnerable in the multi-level signal. Besides, the proposed BRPD has a unique lock point with an adaptive DFE, unlike conventional Mueller-Muller PD. A prototype chip fabricated in 40 nm CMOS technology occupies an active area of 0.24 mm2. The proposed PAM-4 RX achieves the bit-error-rate less than 10-11 in 48 Gb/s and the power efficiency of 2.42 pJ/b.๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์†, ์ €์ „๋ ฅ์œผ๋กœ ๋™์ž‘ํ•˜๋Š” ์œ ์„  ์ˆ˜์‹ ๊ธฐ์˜ ์„ค๊ณ„์— ๋Œ€ํ•ด ์„ค๋ช…ํ•˜๊ณ  ์žˆ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๋งํ•˜๋ฉด, ์˜คํ”„์…‹ ์ƒ์‡„, ๋ณ‘ํ•ฉ๋œ ์„œ๋จธ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฐ์ • ํ”ผ๋“œ๋ฐฑ ๋“ฑํ™”๊ธฐ ๊ธฐ์ˆ , ํ™•๋ฅ ์  ๋ณด์šฐ ๋ ˆ์ดํŠธ ํด๋Ÿญ๊ณผ ๋ฐ์ดํ„ฐ ๋ณต์›๊ธฐ, ๊ทธ๋ฆฌ๊ณ  ๋‹ค์ค‘ ๋ ˆ๋ฒจ ์‹ ํ˜ธ์— ์ ํ•ฉํ•œ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ์งธ๋กœ, ์ ์‘ ์˜คํ”„์…‹ ์ œ๊ฑฐ ๋ฐ ๋ณ‘ํ•ฉ๋œ ์„œ๋จธ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฐ์ • ํ”ผ๋“œ๋ฐฑ ๋“ฑํ™”๊ธฐ๋ฅผ ๊ฐ–์ถ˜ ์ˆ˜์‹ ๊ธฐ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ์ ์‘ ์˜คํ”„์…‹ ์ œ๊ฑฐ ์—”์ง„์€ ์ž„์˜์˜ ๋ฐ์ดํ„ฐ ์ŠคํŠธ๋ฆผ์˜ ์ƒ˜ํ”Œ๋ง ๋ฐ์ดํ„ฐ, ์—์ง€ ์ถœ๋ ฅ์„ ๊ฒ€์‚ฌํ•˜์—ฌ ๋ฐ์ดํ„ฐ ๊ฒฝ๋กœ ์ƒ์˜ ์˜คํ”„์…‹์„ ์ œ๊ฑฐํ•œ๋‹ค. ๋˜ํ•œ ํ•˜ํ”„ ๋ ˆ์ดํŠธ ๊ตฌ์กฐ์˜ ๋ณ‘ํ•ฉ๋œ ์„œ๋จธ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฐ์ • ํ”ผ๋“œ๋ฐฑ ๋“ฑํ™”๊ธฐ๋Š” ์ „๋ ฅ์˜ ์‚ฌ์šฉ๊ณผ ํ•˜๋“œ์›จ์–ด์˜ ๋ณต์žก์„ฑ์„ ์ค„์ธ๋‹ค. 40 nm CMOS ๊ธฐ์ˆ ๋กœ ์ œ์ž‘๋œ ํ”„๋กœํ† ํƒ€์ž… ์นฉ์€ 0.083 mm2 ์˜ ๋ฉด์ ์„ ๊ฐ€์ง„๋‹ค. ์ ์‘ ์˜คํ”„์…‹ ์ œ๊ฑฐ๊ธฐ ๋•๋ถ„์— ์ œ์•ˆ๋œ ์ˆ˜์‹ ๊ธฐ๋Š” 10-12 ๋ฏธ๋งŒ์˜ BER์„ ๋‹ฌ์„ฑํ•œ๋‹ค. ๋˜ํ•œ ์ œ์•ˆ๋œ ์ˆ˜์‹ ๊ธฐ๋Š” 5GHz์—์„œ 27 dB์˜ ๋กœ์Šค๋ฅผ ๊ฐ–๋Š” ์ฑ„๋„์—์„œ 10 Gb/s์˜ ์†๋„์—์„œ 18.6 mW๋ฅผ ์†Œ๋น„ํ•˜๋ฉฐ 0.068 pJ/b/dB์˜ FoM์„ ๋‹ฌ์„ฑํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ๋กœ, ๋ณด์šฐ ๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๊ฐ€ ์žˆ๋Š” 40 nm CMOS ์ˆ˜์‹ ๊ธฐ๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ˆ˜์‹ ๊ธฐ์—๋Š” ๋‘๊ฐœ์˜ ๋ณด์šฐ ๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋ฅผ ํฌํ•จํ•œ๋‹ค. ํ•˜๋‚˜๋Š” ํ™•๋ฅ ๋ก ์  ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•˜๋Š” ๋ณด์šฐ ๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ์ด๋‹ค. ๋ณด์šฐ ๋ ˆ์ดํŠธ ํด๋Ÿญ ๋ฐ์ดํ„ฐ ๋ณต์›๊ธฐ์˜ ์žฅ์  ๋•๋ถ„์— ์—์ง€ ์ƒ˜ํ”Œ๋ง ํด๋Ÿญ์„ ์‚ฌ์šฉํ•˜์ง€ ์•Š์Œ์œผ๋กœ์„œ ํŒŒ์›Œ์˜ ์†Œ๋ชจ์™€ ํ•˜๋“œ์›จ์–ด์˜ ๋ณต์žก์„ฑ์„ ์ค„์˜€๋‹ค. ๋˜ํ•œ ํ™•๋ฅ ์  ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋Š” ์ˆ˜์ง ์•„์ด ์˜คํ”„๋‹์„ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ์ตœ์ ์˜ ์œ„์ƒ ์ง€์ ์„ ์ฐพ์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‹ค๋ฅธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋Š” ๋‹ค์ค‘ ๋ ˆ๋ฒจ ์‹ ํ˜ธ์— ์ ํ•ฉํ•œ ๋ฐฉ์‹์ด๋‹ค. ์‹ฌ๋ณผ ๊ฐ„ ๊ฐ„์„ญ์ด ๋‹ค์ค‘ ๋ ˆ๋ฒจ ์‹ ํ˜ธ์— ๋งค์šฐ ์ทจ์•ฝํ•œ ๋ฌธ์ œ๊ฐ€ ์žˆ๋”๋ผ๋„ ์ œ์•ˆ๋œ ๋‹ค์ค‘ ๋ ˆ๋ฒจ ์‹ ํ˜ธ์šฉ ๋ณด์šฐ ๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋Š” ์ˆ˜์ง ์•„์ด ๋งˆ์ง„์„ ํ™•๋ณดํ•œ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ ์ œ์•ˆ๋œ ๋ณด์šฐ ๋ ˆ์ดํŠธ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ๋Š” ๊ธฐ์กด์˜ ๋ฎฌ๋Ÿฌ-๋ฎ๋Ÿฌ ์œ„์ƒ ๊ฒ€์ถœ๊ธฐ์™€ ๋‹ฌ๋ฆฌ ์ ์‘ํ˜• ๊ฒฐ์ • ํ”ผ๋“œ๋ฐฑ ๋“ฑํ™”๊ธฐ๊ฐ€ ์žˆ๋”๋ผ๋„ ์œ ์ผํ•œ ๋ฝ ์ง€์ ์„ ๊ฐ–๋Š”๋‹ค. ํ”„๋กœํ† ํƒ€์ž… ์นฉ์€ 0.24mm2์˜ ๋ฉด์ ์„ ๊ฐ€์ง„๋‹ค. ์ œ์•ˆ๋œ PAM-4 ์ˆ˜์‹ ๊ธฐ๋Š” 48 Gb/s์˜ ์†๋„์—์„œ 10-11 ๋ฏธ๋งŒ์˜ BER์„ ๊ฐ€์ง€๊ณ , 2.42 pJ/b์˜ FoM์„ ๊ฐ€์ง„๋‹ค.CHAPTER 1 INTRODUCTION 1 1.1 MOTIVATION 1 1.2 THESIS ORGANIZATION 5 CHAPTER 2 BACKGROUNDS 6 2.1 BASIC ARCHITECTURE IN SERIAL LINK 6 2.1.1 SERIAL COMMUNICATION 6 2.1.2 CLOCK AND DATA RECOVERY 8 2.1.3 MULTI-LEVEL PULSE-AMPLITUDE MODULATION 10 2.2 EQUALIZER 12 2.2.1 EQUALIZER OVERVIEW 12 2.2.2 DECISION-FEEDBACK EQUALIZER 15 2.2.3 ADAPTIVE EQUALIZER 18 2.3 CLOCK RECOVERY 21 2.3.1 2X OVERSAMPLING PD ALEXANDER PD 22 2.3.2 BAUD-RATE PD MUELLER MULLER PD 25 CHAPTER 3 AN ADAPTIVE OFFSET CANCELLATION SCHEME AND SHARED SUMMER ADAPTIVE DFE 28 3.1 OVERVIEW 28 3.2 AN ADAPTIVE OFFSET CANCELLATION SCHEME AND SHARED-SUMMER ADAPTIVE DFE FOR LOW POWER RECEIVER 31 3.3 SHARED SUMMER DFE 37 3.4 RECEIVER IMPLEMENTATION 42 3.5 MEASUREMENT RESULTS 45 CHAPTER 4 PAM-4 BAUD-RATE DIGITAL CDR 51 4.1 OVERVIEW 51 4.2 OVERALL ARCHITECTURE 53 4.2.1 PROPOSED BAUD-RATE CDR ARCHITECTURE 53 4.2.2 PROPOSED ANALOG FRONT-END STRUCTURE 59 4.3 STOCHASTIC PHASE DETECTION PAM-4 CDR 64 4.3.1 PROPOSED STOCHASTIC PHASE DETECTION 64 4.3.2 COMPARISON OF THE STOCHASTIC PD WITH SS-MMPD 70 4.4 PHASE DETECTION FOR MULTI-LEVEL SIGNALING 73 4.4.1 PROPOSED BAUD-RATE PHASE DETECTOR FOR MULTI-LEVEL SIGNAL 73 4.4.2 DATA LEVEL AND DFE COEFFICIENT ADAPTATION 79 4.4.3 PROPOSED PHASE DETECTOR 84 4.5 MEASUREMENT RESULT 88 4.5.1 MEASUREMENT OF THE PROPOSED STOCHASTIC BAUD-RATE PHASE DETECTION 94 4.5.2 MEASUREMENT OF THE PROPOSED BAUD-RATE PHASE DETECTION FOR MULTI-LEVEL SIGNAL 97 CHAPTER 5 CONCLUSION 103 BIBLIOGRAPHY 105 ์ดˆ ๋ก 109๋ฐ•

    Application of adaptive antenna techniques to future commercial satellite communication

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    The purpose of this contract was to identify the application of adaptive antenna technique in future operational commercial satellite communication systems and to quantify potential benefits. The contract consisted of two major subtasks. Task 1, Assessment of Future Commercial Satellite System Requirements, was generally referred to as the Adaptive section. Task 2 dealt with Pointing Error Compensation Study for a Multiple Scanning/Fixed Spot Beam Reflector Antenna System and was referred to as the reconfigurable system. Each of these tasks was further sub-divided into smaller subtasks. It should also be noted that the reconfigurable system is usually defined as an open-loop system while the adaptive system is a closed-loop system. The differences between the open- and closed-loop systems were defined. Both the adaptive and reconfigurable systems were explained and the potential applications of such systems were presented in the context of commercial communication satellite systems

    Applications of Adaptive Filtering

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