System Modeling for Active Noise Control with Reservoir Computing

This paper investigates the use of reservoir computing for active noise control (ANC). It is shown that the ANC problem can be solved by a concatenation of physically present subsystems. These subsystems can be modelled by reservoirs that are trained, using one shot learning. This approach is compared to genetic algorithms tuning a Volterra filter. Experimental results show that our approach works well as system model, meaning that a reservoir trained on white noise performs good on other input signals as well. This is a major advantage over genetic algorithms that generalize rather badly. Furthermore, our approach needs less data and this data can be gathered in one experiment only

Review of active noise control techniques with emphasis on sound quality enhancement

The traditional active noise control design aims to attenuate the energy of residual noise, which is indiscriminative in the frequency domain. However, it is necessary to retain residual noise with a specified spectrum to satisfy the requirements of human perception in some applications. In this paper, the evolution of active noise control and sound quality are briefly discussed. This paper emphasizes on the advancement of active noise control method in the past decades in terms of enhancing the sound quality

Active control of noise transmitted from barriers

Active noise cancellation is a unique approach that helps passive noise control in reducing sound levels at low frequencies; nevertheless, successful use of active noise cancellation necessitates performing numerous and tedious experiments together with defining several parameters properly. The locations and quantity of active control system transducers are among these parameters. The present research provides a comprehensive framework for placing control sources and error microphones near a noise barrier in order to improve its efficiency in both narrowband and broadband noise spectra. To accomplish this, the appropriate locations for the control sources are first determined using a repetitive computation method, and then the optimizations are completed by determining the best position for the error microphone. Several alternative transducer locations near the barrier are incorporated in the repetitive computation, and the optimal sites for the control sources and error microphones are found using two-step optimization methods as well as the genetic algorithms approach. The findings reveal that the best places to put the control sources are on the incident side, below the barrier's edge, and the best locations to place the error microphones are on the shadow side, as close as possible to the target area. The effect of ground reflection on the efficiency of the active noise control system is also investigated, and it is discovered that while ground reflection has no significant effect on the performance of the active noise control system for broadband frequency ranges, it does reduce the control system's efficiency at tonal noises. In order to optimize more parameters, further calculations are performed based on the genetic optimizer. The output of the GA calculations found new configurations for the control units that result in higher noise level reduction at the target area. In addition to the active noise barrier, the application of active noise cancellation for open windows as a particular case of the barrier is explored as a particular case of the barrier. Different arrangements are studied for the control units close to the open windows, including linear, boundary, and planar control arrangements. The effect of several parameters such as the incident angle of noise waves, the distance between error microphones and the opening, and the number of control units are investigated. The results demonstrate that the active noise control system with obliqued linear placements of transducers have higher performance than the other arrangements. Furthermore, when the frequency and incident angle increase, the effectiveness of active noise reduction decreases.La cancelación activa de ruido es un enfoque único que ayuda al control pasivo del ruido a reducir los niveles de sonido a bajas frecuencias; sin embargo, el uso exitoso de la cancelación activa de ruido requiere la realización de numerosos y tediosos experimentos junto con la definición adecuada de varios parámetros. La ubicación y la cantidad de transductores del sistema de control activo se encuentran entre estos parámetros. La presente investigación proporciona un marco completo para colocar fuentes de control y micrófonos de error cerca de una barrera de ruido con el fin de mejorar su eficiencia en espectros de ruido de banda estrecha y banda ancha. Para lograr esto, primero se determinan las ubicaciones apropiadas para las fuentes de control usando un método de cálculo repetitivo, y luego se completan las optimizaciones determinando la mejor posición para el micrófono de error. Varias ubicaciones de transductores alternativas cerca de la barrera se incorporan en el cálculo repetitivo, y los sitios óptimos para las fuentes de control y los micrófonos de error se encuentran utilizando métodos de optimización de dos pasos, así como el enfoque de algoritmos genéticos. Los hallazgos revelan que los mejores lugares para colocar las fuentes de control están en el lado del incidente, debajo del borde de la barrera, y los mejores lugares para colocar los micrófonos de error están en el lado de la sombra, lo más cerca posible del área objetivo. También se investiga el efecto de la reflexión del suelo sobre la eficiencia del sistema de control de ruido activo, y se descubre que si bien la reflexión del suelo no tiene un efecto significativo en el rendimiento del sistema de control de ruido activo para rangos de frecuencia de banda ancha, sí reduce el rendimiento del sistema de control. eficiencia en ruidos tonales. Para optimizar más parámetros, se realizan más cálculos basadosen el optimizador genético. El resultado de los cálculos de GA encontró nuevas configuraciones para las unidades de control que dan como resultado una mayor reducción del nivel de ruido en el área objetivo. Además de la barrera de ruido activa, se explora la aplicación de la cancelación de ruido activa para ventanas abiertas como un caso particular de la barrera. Se estudian cuatro disposiciones para las unidades de control cercanas a las ventanas abiertas. Las unidades de control en una configuración de límite se colocan en el borde de la abertura, mientras que en el control plano, se ubican en la superficie de la abertura. En una configuración de contorno, las unidades de control se colocan en el borde de la abertura, mientras que en un diseño plano, se colocan en la superficie de la abertura. Se investiga el efecto de varios parámetros como el ángulo de incidencia de las ondas de ruido, la distancia entre los micrófonos de error y la apertura, y el número de unidades de control. Los resultados demuestran que el sistema de control de ruido activo con configuración plana tiene un rendimiento más alto que el control de límites. Además, cuando la frecuencia y el ángulo de incidencia aumentan, la eficacia de la reducción activa del ruido disminuye.Postprint (published version

Development of novel hybrid method and geometrical configuration-based active noise control system for circular cylinder and slat noise prediction and reduction applications

This thesis presents a study about the application of a geometrical configuration-based feedforward adaptive active noise control (ANC) system in the low-frequency range of flow-induced (aeroacoustics) noise cancellation and the investigation on the effects of different geometrical configurations on the cancellation performance in the presence of the residual noise signal magnitude (in decibel) or the average amount of cancellation (in decibel). The first motivation is that according to the literature review, the passive flow control is limited in the practical consideration and the active flow control performs better than the passive flow control, especially for the low-frequency range. Consider the principle of the active flow control is the same as the ANC technique, therefore, it is feasible to apply the ANC technique in cancelling the low-frequency range of the far-field (aeroacoustics) noise, which provides instructions on the future practical experiments. The second motivation is that we want to explore the effects of different geometrical configurations on the cancellation performance and it provides instructions on the implementation in future practical experiments. To predict the far-field (aeroacoustics) noise, the computational fluid dynamics (CFD) and the Ffowcs Williams and Hawkings (FW-H) equations are used separately for unsteady flow calculation and far-field (aeroacoustics) noise prediction. The proposed ANC system is used for the low-frequency range of the far-field (aeroacoustics) noise cancellation. Soft computing techniques and evolutionary-computing-based techniques are employed as the parameter adjustment mechanism to deal with nonlinearities existed in microphones and loudspeakers. The case study about the landing gear noise cancellation in the two-dimensional computational domain is completed. Simulation results validate the accuracy of the obtained acoustic spectrum with reasonable error because of the mesh resolution and computer capacity. It is observed that the two-dimensional approach can only predict discrete values of sound pressure level (SPL) associated with the fundamental frequency (Strouhal number) and its harmonics. Cancellation results demonstrate the cancellation capability of the proposed ANC system for the low-frequency range of far-field (aeroacoustics) noise and reflect that within the reasonable physical distance range, the cancellation performance will be better when the detector is placed closer to the secondary source in comparison with the primary source. This conclusion is the main innovative contribution of this thesis and it provides useful instructions on future practical experiments, but detailed physical distance values must be dependent on individual cases

Development of Novel Techniques to Study Nonlinear Active Noise Control

Active noise control has been a field of growing interest over the past few decades. The challenges thrown by active noise control have attracted the notice of the scientific community to engage them in intense level of research. Cancellation of acoustic noise electronically in a simple and efficient way is the vital merit of the active noise control system. A detailed study about existing strategies for active noise control has been undertaken in the present work. This study has given an insight regarding various factors influencing performance of modern active noise control systems. The development of new training algorithms and structures for active noise control are active fields of research which are exploiting the benefits of different signal processing and soft- computing techniques. The nonlinearity contributed by environment and various components of active noise control system greatly affects the ultimate performance of an active noise canceller. This fact motivated to pursue the research work in developing novel architectures and algorithms to address the issues of nonlinear active noise control. One of the primary focus of the work is the application of artificial neural network to effectively combat the problem of active noise control. This is because artificial neural networks are inherently nonlinear processors and possesses capabilities of universal approximation and thus are well suited to exhibit high performance when used in nonlinear active noise control. The present work contributed significantly in designing efficient nonlinear active noise canceller based on neural network platform. Novel neural filtered-x least mean square and neural filtered-e least mean square algorithms are proposed for nonlinear active noise control taking into consideration the nonlinear secondary path. Employing Legendre neural network led the development of a set new adaptive algorithms such as Legendre filtered-x least mean square, Legendre vi filtered-e least mean square, Legendre filtered-x recursive least square and fast Legendre filtered-x least mean square algorithms. The proposed algorithms outperformed the existing standard algorithms for nonlinear active noise control in terms of steady state mean square error with reduced computational complexity. Efficient frequency domain implementation of some the proposed algorithms have been undertaken to exploit its benefits. Exhaustive simulation studies carried out have established the efficacy of the proposed architectures and algorithms