Control of feedback for assistive listening devices

Acoustic feedback refers to the undesired acoustic coupling between the loudspeaker and microphone in hearing aids. This feedback channel poses limitations to the normal operation of hearing aids under varying acoustic scenarios. This work makes contributions to improve the performance of adaptive feedback cancellation techniques and speech quality in hearing aids. For this purpose a two microphone approach is proposed and analysed; and probe signal injection methods are also investigated and improved upon

A Frequency-Domain Method for Active Acoustic Cancellation of Known Audio Sources

Active noise control (ANC) is a real-time process in which a system measures an external, unwanted sound source and produces a canceling waveform. The cancellation is due to destructive interference by a perfect copy of the received signal phase-shifted by 180 degrees. Existing active noise control systems process the incoming and outgoing audio on a sample-by-sample basis, requiring a high-speed digital signal processor (DSP) and analog-to-digital converters (ADCs) with strict timing requirements on the order of tens of microseconds. These timing requirements determine the maximum sample rate and bit size as well as the maximum attenuation that the system can achieve. In traditional noise cancellation systems, the general assumption is that all unwanted sound is indeterminate. However, there are many instances in which an unwanted sound source is predictable, such as in the case of a song. This thesis presents a method for active acoustic cancellation of a known audio signal using the frequency characteristics of the known audio signal compared to that of a sampled, filtered excerpt of the same known audio signal. In this procedure, we must first correctly locate the sample index for which a measured audio excerpt begins via the cross-correlation function. Next, we obtain the frequency characteristics of both the known source (WAVE file of the song) and the measured unwanted audio by taking the Fast Fourier Transform (FFT) of each signal, and calculate the effective environmental transfer function (degradation function) by taking the ratio of the two complex frequency-domain results. Finally, we attempt to recreate the environmental audio from the known data and produce an inverted, synchronized, and amplitude-matched signal to cancel the audio via destructive interference. Throughout the process, we employ many signal conditioning methods such as FIR filtering, median filtering, windowing, and deconvolution. We illustrate this frequency-domain method in Native Instruments’ LabVIEW running on the Windows operating system, and discuss its reliability, areas for improvement, and potential future applications in mobile technologies. We show that under ideal conditions (unwanted sound is a known white noise source, and microphone, loudspeaker, and environmental filter frequency responses are all perfectly flat), we can achieve a theoretical maximum attenuation of approximately 300 dB. If we replace the white noise source with an actual song and the environmental filter with a low-order linear filter, then we can achieve maximum attenuation in the range of 50-70 dB. However, in a real-world environment, with additional noise and imperfect microphones, speakers, synchronization, and amplitude-matching, we can expect to see attenuation values in the range of 10-20 dB

DISCRETE-TIME ADAPTIVE CONTROL ALGORITHMS FOR REJECTION OF SINUSOIDAL DISTURBANCES

We present new adaptive control algorithms that address the problem of rejecting sinusoids with known frequencies that act on an unknown asymptotically stable linear time-invariant system. To achieve asymptotic disturbance rejection, adaptive control algorithms of this dissertation rely on limited or no system model information. These algorithms are developed in discrete time, meaning that the control computations use sampled-data measurements. We demonstrate the effectiveness of algorithms via analysis, numerical simulations, and experimental testings. We also present extensions to these algorithms that address systems with decentralized control architecture and systems subject to disturbances with unknown frequencies

Wave-based sensor, actuator and optimizer

Programa doutoral em Sistemas Avançados de Engenharia para a Indústria (AESI)A presente tese explora a utilização de ondas para abordar dois desafios significativos na indústria automóvel. O primeiro desafio consiste no desenvolvimento de um sistema de cancelamento ativo de ruído (ANC) que possa reduzir os ruídos não estacionários no compartimento de passageiros de um veículo. O segundo desafio é criar uma metodologia de conceção ótima para sensores de posição indutivos capazes de medir deslocamentos lineares, rotacionais e angulares. Para abordar o primeiro desafio, foi desenvolvido de um sistema ANC onde wavelets foram combinadas com um banco de filtros adaptativos. O sistema foi implementado em uma FPGA, e testes demonstraram que o sistema pode reduzir o ruído não estacionário em um ambiente acústico aberto e não controlado em 9 dB. O segundo desafio foi abordado através de uma metodologia que combina um algoritmo genético com um método numérico rápido para otimizar um sensor de posição indutivo. O método numérico foi usado para simular o campo eletromagnético associado à geometria do sensor, permitindo a maximização da corrente induzida nas bobinas recetoras e a minimização da não-linearidade no sensor. A minimização da não-linearidade foi conseguida através do desenho (layout) das bobinas que compõem o sensor. Sendo este otimizado no espaço de Fourier através da adição de harmónicos apropriados na geometria. As melhores geometrias otimizadas apresentaram uma não-linearidade inferior a 0,01% e a 0,25% da escala total para os sensores de posição angular e linear, respetivamente, sem calibração por software. O sistema ANC proposto tem o potencial de melhorar o conforto dos ocupantes do veículo, reduzindo o ruído indesejado dentro do compartimento de passageiros. Isso poderia reduzir o uso de materiais de isolamento acústico no veículo, levando a um veículo mais leve e, em última análise, a uma redução no consumo de energia. A metodologia desenvolvida para sensores de posição indutivos contribui para o estado da arte de sensores de posição eficientes e económicos, o que é crucial para os requisitos complexos da indústria automóvel. Essas contribuições têm implicações para o desenho de sistemas automotivos, com requisitos de desempenho e considerações ambientais e económicas.This thesis explores the use of waves to tackle two major engineering challenges in the automotive industry. The first challenge is the development of an Active Noise Cancelling (ANC) system that can effectively reduce non-stationary noise inside a vehicle’s passenger compartment. The second challenge is the optimization of an inductive position sensor design methodology capable of measuring linear, rotational, and angular displacements. To address the first challenge, this work designs an ANC system that employs wavelets combined with a bank of adaptive filters. The system was implemented in an FPGA, and field tests demonstrate its ability to reduce non-stationary noise in an open and uncontrolled acoustic environment by 9 dB. The second challenge was tackled by proposing a new approach that combines a genetic algorithm with a fast and lightweight numerical method to optimize the geometry of an inductive position sensor. The numerical method is used to simulate the sensor’s electromagnetic field, allowing for the maximization of induced current on the receiver coils while minimizing the sensor’s non-linearity. The non-linearity minimization was achieved through its unique sensor’s coils design optimized in the Fourier space by adding the appropriate harmonics to the coils’ geometry. The best optimized geometries exhibited a non-linearity of less than 0.01% and 0.25% of the full scale for the angular and linear position sensors, respectively. Both results were achieved without the need for signal calibration or post-processing manipulation. The proposed ANC system has the potential to enhance the comfort of vehicle occupants by reducing unwanted noise inside the passenger compartment. Moreover, it has the potential to reduce the use of acoustic insulation materials in the vehicle, leading to a lighter vehicle and ultimately reducing energy consumption. The developed methodology for inductive position sensors represents a state-of-the-art contribution to efficient and cost-effective position sensor design, which is crucial for meeting the complex requirements of the automotive industry.I would like to thank the Fundação para a Ciência e Tecnologia (FCT) and Bosch Car Multimedia for funding my PhD (grant PD/BDE/142901/2018)

Active disturbance cancellation in nonlinear dynamical systems using neural networks

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

Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Theory and applications of delta-sigma analogue-to-digital converters without negative feedback

Analog-to-digital converters play a crucial role in modern audio and communication design. Conventional Nyquist converters are suitable only for medium resolutions and require analog components that are precise and highly immune to noise and interference. In contrast, oversampling converters can achieve high resolutions (>20bits) and can be implemented using straightforward, high-tolerance analog components. In conventional oversampled modulators, negative feedback is applied in order to control the dynamic behavior of a system and to realize the attenuation of the quantization noise in the signal band due to noise shaping. However, feedback can also introduce undesirable effects such as limit cycles, jitter problems in continuous-time topologies, and infinite impulse responses. Additionally, it increases the system complexity due to extra circuit components such as nonlinear multi-bit digital-to-analog converters in the feedback path. Moreover, in certain applications such as wireless, biomedical sensory, or microphone implementations feedback cannot be applied. As a result, the main goal of this thesis is to develop sigma-delta data converters without feedback. Various new delta-sigma analog-to-digital converter topologies are explored their mathematical models are presented. Simulations are carried out to validate these models and to show performance results. Specifically, two topologies, a first-order and a second-order oscillator-based delta-sigma modulator without feedback are described in detail. They both can be implemented utilizing VCOs and standard digital gates, thus requiring only few components. As proof of concept, two digital microphones based on these delta-sigma converters without feedback were implemented and experimental results are given. These results show adequate performance and provide a new approach of measuring

Theory and Design of Spatial Active Noise Control Systems

The concept of spatial active noise control is to use a number of loudspeakers to generate anti-noise sound waves, which would cancel the undesired acoustic noise over a spatial region. The acoustic noise hazards that exist in a variety of situations provide many potential applications for spatial ANC. However, using existing ANC techniques, it is difficult to achieve satisfying noise reduction for a spatial area, especially using a practical hardware setup. Therefore, this thesis explores various aspects of spatial ANC, and seeks to develop algorithms and techniques to promote the performance and feasibility of spatial ANC in real-life applications. We use the spherical harmonic analysis technique as the basis for our research in this work. This technique provides an accurate representation of the spatial noise field, and enables in-depth analysis of the characteristics of the noise field. Incorporating this technique into the design of spatial ANC systems, we developed a series of algorithms and methods that optimizes the spatial ANC systems, towards both improving noise reduction performance and reducing system complexity. Several contributions of this work are: (i) design of compact planar microphone array structures capable of recording 3D spatial sound fields, so that the noise field can be monitored with minimum physical intrusion to the quiet zone, (ii) derivation of a Direct-to-Reverberant Energy Ratio (DRR) estimation algorithm which can be used for evaluating reverberant characteristics of a noisy environment, (iii) propose a few methods to estimate and optimize spatial noise reduction of an ANC system, including a new metric for measuring spatial noise energy level, and (iv) design of an adaptive spatial ANC algorithm incorporating the spherical harmonic analysis technique. The combination of these contributions enables the design of compact, high performing spatial ANC systems for various applications