Active structural acoustic control has previously been used to reduce low-frequency sound radiation from relatively simple laboratory structures. However, significant implementation issues have to be addressed before active control can be used on large, complex structures such as an aircraft fuselage. The purpose of this project is to extend decentralized structural control systems from individual bays to more realistic airframe structures. In addition, to make this investigation more applicable to industry, potential control strategies are evaluated using a realistic aft-cabin disturbance identified from flight test data. This work focuses on decentralized control, which implies that each control unit is designed and implemented independently. While decentralized control systems are relatively scalable, performance can be limited due to the destabilizing interaction between neighboring controllers. An in-depth study of this problem demonstrates that the modeling error introduced by neighboring controllers can be expressed as the product of the complementary sensitivity function of the neighboring control unit multiplied by a term that quantifies the diagonal dominance of the plant. This understanding can be used to improve existing control strategies. For instance, decentralized performance can often be improved by penalizing control effort at the zeros of the local control model. This stabilizes each control unit and reduces the modeling error induced on neighboring controllers. Additional analyses show that the performance of decentralized model-based control systems can be improved by augmenting the structural damping using robust, low-authority control strategies such as direct velocity feedback and positive position feedback. Increasing the structural damping can supplement the performance of the model-based control strategy and reduce the destabilizing interaction between neighboring control units. Instead of using low-authority controllers to stabilize the decentralized control system, another option is to modify the model-based design. Specifically, an iterative approach is developed and validated using real-time control experiments performed on a structural-acoustic system with poles close to the stability boundary, non-minimum phase zeros, and unmodeled dynamics. Experiments demonstrate that the iterative control strategy, which combines frequency-shaped linear quadratic Gaussian (LQG) control with loop transfer recovery (LTR), is capable of achieving 12dB peak reductions and a 3.6dB integrated reduction in radiated sound power from a rib-stiffened aluminum panel. / Ph. D.

In this work, the potential for a smart foam actuator in controlling interior cabin noise due to a turbulent boundary layer excitation has been experimentally demonstrated. A smart foam actuator is a device comprised of sound absorbing foam with an embedded distributed piezoelectric layer (PVDF) designed to operate over a broad range of frequencies. The acoustic foam acts as a passive absorber and targets the high frequency content, while the PVDF serves as the active component and is used to overcome the limitations of the acoustic foam at low frequencies. The fuselage skin of an aircraft was represented by an experimental test panel in an anechoic box mounted to the side of a wind tunnel. The rig was used to simulate turbulent boundary layer noise transmission into and aircraft cabin. An active noise control (ANC) methodology was employed by covering the test panel with the smart foam actuators and driving them to generate a secondary sound field. This secondary sound field, when superimposed with the panel radiation, resulted in a reduction in overall sound in the anechoic box. An adaptive feedforward filtered-x Least-Mean-Squared (LMS) control algorithm was used to drive the smart foam actuators to reduce the sound pressure levels at an array of microphones. Accelerometers measured the response of the test panel and were used as the reference signal for the feedforward algorithm. A detailed summary of the smart foam actuator control performance is presented for two separate low speed wind tunnel facilities with speeds of Mach 0.1 and Mach 0.2 and a single high speed tunnel facility operating at Mach 0.8 and Mach 2.5. / Master of Science

Smart foam is a composite noise control treatment that consists of a distributed piezoelectric actuator, known as polyvinylidene fluoride (PVDF), embedded within a layer of partially-reticulated polyurethane foam. The principal function of smart foam is to yield broadband sound attenuation. Passive acoustic foams are a very reliable high-frequency sound reduction method. With regard to smart foam, the embedded piezoelectric actuator is introduced to overcome the limitations of the passive foam in the low-frequency region. The piezoelectric actuator excites the structural and acoustic phases of the foam when driven by an externally supplied control voltage. This generates a secondary acoustic field which destructively interacts with the acoustic field created by a primary noise source. Initial experiments employ the composite "active/passive" treatment to yield attenuation of piston sound radiation. For this simple source, the global farfield pressure is minimized according to the feedforward, Filtered-x LMS control algorithm using one error sensor. Significant broadband sound attenuation is obtained. A more advanced noise control problem is investigated which minimizes plate radiation. The vibrating plate has a distributed modal response requiring a collective array of independently-phased smart foam actuators to yield reduction of the radiated sound power. This is accomplished by minimizing the sound pressure at an array of nearfield microphones. Good broadband sound power reduction is obtained using a MIMO (multiple-input/multiple-output) Filtered-x LMS control scheme. Various techniques for improving smart foam's acoustic control authority are identified during manufacturing and finite element modeling. of the actuator. These improved smart foam actuators are employed as an active/passive liner to suppress the transverse propagating acoustic modes within an anechoically-terminated rectangular duct. A section of a duct wall is lined with an array of smart foam and the sound downstream of the control actuators is minimized at several error microphones. Successful harmonic and broadband noise control is achieved. A full-scale numerical model of the duct acoustic control application is presented based on the finite element method. The purpose of the model is to study the sensitivity of this active/passive control approach relative to the spatial distribution of control channels and error sensors. A comparison of the numerical and experimental results yields similar trends. / Ph. D.

Adaptive feedforward control of any physical system, acoustical, vibrational or other, requires what is termed as an uncontrollable coherent reference signal. That is, a signal which is highly representative (coherent) of the disturbance to be controlled which is not affected by the control actuator itself. Creating the <i>coherent</i> portion of this requirement for a certain class of problems is the motivation of this work. Most physical disturbances do not originate from a single source, but rather maintain contributions from a number of (possibly) correlated paths. For engineers who have access to only a single-input single-output (SISO) adaptive controller, the multi-source disturbance presents a difficult design issue. Simply adding the references in a linear combination can result in a signal which is not coherent at any frequency. Appropriately amplifying and suppressing coherent and incoherent signals prior to their linear combination can result in a signal which accurately represents the disturbance at all frequencies. This is precisely the task that the newly developed coherent output power (COP) filters perform. By calculating the coherent (or partial coherent) output power of each of the candidate references before control occurs, frequency domain filters are designed to remove incoherent portions of each signal. The advantages of performing the COP filtering procedure are very apparent when compared to the simple linear combination of signals. Coherence, and thus control performance, can be drastically improved. The COP filtering technique offers a means for system identification and computational savings not apparent in the conventional adaptive array, which solves the same multi-source problem. / Master of Science

Low frequency noise is a common problem in aircraft and launch vehicles. New technologies must be investigated to reduce this noise while contributing minimal weight to the structure. This thesis investigates passive and active control methods to improve low frequency sound absorption and transmission loss using acoustic metamaterials. The acoustic metamaterials investigated consist of poro-elastic acoustic heterogeneous (HG) metamaterials and microperforated (MPP) acoustic metamaterials. HG metamaterials consist of poro-elastic material with a periodic arrangement of embedded masses acting as an array of mass-spring- damper systems. MPP acoustic metamaterials consist of periodic layers of micro-porous panels embedded in poro-elastic material. This thesis examines analytically, experimentally, and numerically the behavior of acoustic metamaterials compared to a baseline poro-elastic sample. The development of numerical techniques using finite element analysis will aid in understanding the physics behind their functionality and will influence their design. Design studies are performed to understand the effects of varying the density, size, shape, and placement of the embedded masses as well as the location and distribution of microperforated panels in poro- elastic material. An active HG metamaterial is investigated, consisting of an array of active masses embedded within poro-elastic material. Successful tonal and broadband noise control is achieved using a feedforward, filtered-x LMS control algorithm to minimize the downstream sound pressure level. Low-frequency absorption and transmission loss is successfully increased in the critical frequency range below 500 Hz. Acoustic metamaterials are compact compared to conventional materials and find applications in controlling low-frequency sound radiation in aircraft and launch vehicles. / Master of Science

This dissertation is concerned with the active control of local sound fields, as applied to an active headrest system. Using loudspeakers and microphones, an active headrest is capable of attenuating ambient noise and providing a comfortable acoustic environment for an occupant. A finite element (FE) model of an active headrest is built and analyzed such that the expected noise reduction levels could be quantified for various geometries as well as primary sound field conditions. Both plane wave and diffuse primary sound fields are considered and it is shown that the performance deteriorates for diffuse sound fields. It is then demonstrated that virtual sensing can greatly improve the spatial extent of the quiet zones as well as the attenuation levels. A prototype of the active headrest was constructed, with characteristics similar to those of the FE model, and tested in both anechoic and reverberant sound fields. Multichannel feedforward and feedback control architectures are implemented in real-time and it is shown that adaptive feedback systems are capable of attenuating band-limited disturbances. The spatial attenuation pattern surrounding the head is also measured by shifting the head to various positions and measuring the attenuation at the ears. Two virtual sensing techniques are compared in both feedback and feedforward architectures. The virtual microphone arrangement, which assumes that the primary sound field is equivalent at the physical and virtual locations, results in the best performance when used in a feedback system attenuating broadband disturbances. The remote microphone technique, which accounts for the transfer response between the physical and virtual locations, offers the best performance for tonal primary sound fields. In broadband sound fields, a causal relationship rarely exists between the physical and virtual microphones, resulting in poor performance. / PHD

In this thesis, the design and implementation of a Portable Feedback Active Noise Controller Headphone System, which is based on Texas Instruments TMS320VC5416PGE120 Fixed Point DSP, is described. Problems resulted from fixed-point implementation of LMS algorithm and delays existing in digital ANC implementation are determined. Effective solutions to overcome the aforementioned problems are proposed based on the literature survey. Design of the DSP based control card is explained and crucial points about analog-digital-mixed board design for noise sensitive applications are explained. Filtered input LMS algorithm, filtered input normalized LMS algorithm and filtered input sign-sign LMS algorithm are implemented as adaptation algorithms. The advantages and disadvantages of using modified LMS algorithms are indicated. The selection of the parameters of these algorithms is based on theoretical results and experiments. The real time performances of different adaptation algorithms are compared with each other as well as with a commercial analog ANC headphone under different types of artificial and natural noise signals. Moreover, practical conditions such as put on - put off case and dynamic range overflow case are handled with additional software implementations. It is shown that adaptive ANC systems improve the noise reduction significantly when the noise is within a narrow frequency range and this reduction can be applied to a wider frequency range. It is also shown that the problems of digitally implemented adaptive filters which are based on tracking capability, stability, dynamic range and portability can be fixed to challenge with the analog commercial ANC systems.

Achieving a low noise level is of great interest to the forest machine industry. Traditionally this is obtained by using passive noise reduction, i.e. by using materials for sound isolation and sound absorption. Especially designs to attenuate low frequency noise tend to be bulky and impractical from an installation point of view. An alternative solution to the problem is to use active noise control (ANC). The basic principle of ANC is to generate an anti-noise signal designed to destructively interfere with the unwanted noise. In this thesis two algorithms (Feedback FxLMS and Feedforward FxLMS) are implemented and evaluated for use in the ANC-system. The ANC-system is tuned to the specific environment in the driver’s cabin of a Komatsu forest machine. The algorithms are first tested in a simulated environment and then in real-time inside a forest machine. Simulations are made both in Matlab and in C using both generated signals and recorded signals. The C code is implemented on the Analog Devices Blackfin DSP card BF526. The result showed a significantly reduction of the sound pressure level (SPL) in the driver’s cabin. The noise attenuation obtained using the Feedback FxLMS was approximately 14 dB for a tonal 100 Hz signal and 11 dB using recorded engine noise from a forest machine at 850 rpm.

The design of a battery-powered, portable headphone active noise control system with TI TMS320C5416 DSP is described. The preliminary implementation of the system on a C5416 DSK is also explained. The problems of fixed-point implementation are described and solutions are proposed. Sign-sign Fx-LMS algorithm with a dead-zone is introduced and used as the adaptation algorithm. Effective use of dynamic range to improve the accuracy in filtering operations is discussed. Details of the designed battery-powered DSP board are given and board software development process is explained. The DSK system and designed portable system is compared against two commercially available analog systems under three different types of noises / composition of tones, drill noise and propeller plane cabin noise. The results reveal that adaptive system has better overall performance.

[EN] The field of audio signal processing has undergone a major development in recent years. Both the consumer and professional marketplaces continue to show growth in audio applications such as immersive audio schemes that offer optimal listening experience, intelligent noise reduction in cars or improvements in audio teleconferencing or hearing aids. The development of these applications has a common interest in increasing or improving the number of discrete audio channels, the quality of the audio or the sophistication of the algorithms. This often gives rise to problems of high computational cost, even when using common signal processing algorithms, mainly due to the application of these algorithms to multiple signals with real-time requirements. The field of High Performance Computing (HPC) based on low cost hardware elements is the bridge needed between the computing problems and the real multimedia signals and systems that lead to user's applications. In this sense, the present thesis goes a step further in the development of these systems by using the computational power of General Purpose Graphics Processing Units (GPGPUs) to exploit the inherent parallelism of signal processing for multichannel audio applications. The increase of the computational capacity of the processing devices has been historically linked to the number of transistors in a chip. However, nowadays the improvements in the computational capacity are mainly given by increasing the number of processing units and using parallel processing. The Graphics Processing Units (GPUs), which have now thousands of computing cores, are a representative example. The GPUs were traditionally used to graphic or image processing, but new releases in the GPU programming environments such as CUDA have allowed the use of GPUS for general processing applications. Hence, the use of GPUs is being extended to a wide variety of intensive-computation applications among which audio processing is included. However, the data transactions between the CPU and the GPU and viceversa have questioned the viability of the use of GPUs for audio applications in which real-time interaction between microphones and loudspeakers is required. This is the case of the adaptive filtering applications, where an efficient use of parallel computation in not straightforward. For these reasons, up to the beginning of this thesis, very few publications had dealt with the GPU implementation of real-time acoustic applications based on adaptive filtering. Therefore, this thesis aims to demonstrate that GPUs are totally valid tools to carry out audio applications based on adaptive filtering that require high computational resources. To this end, different adaptive applications in the field of audio processing are studied and performed using GPUs. This manuscript also analyzes and solves possible limitations in each GPU-based implementation both from the acoustic point of view as from the computational point of view. / [ES] El campo de procesado de señales de audio ha experimentado un desarrollo importante en los últimos años. Tanto el mercado de consumo como el profesional siguen mostrando un crecimiento en aplicaciones de audio, tales como: los sistemas de audio inmersivo que ofrecen una experiencia de sonido óptima, los sistemas inteligentes de reducción de ruido en coches o las mejoras en sistemas de teleconferencia o en audífonos. El desarrollo de estas aplicaciones tiene un propósito común de aumentar o mejorar el número de canales de audio, la propia calidad del audio o la sofisticación de los algoritmos. Estas mejoras suelen dar lugar a sistemas de alto coste computacional, incluso usando algoritmos comunes de procesado de señal. Esto se debe principalmente a que los algoritmos se suelen aplicar a sistemas multicanales con requerimientos de procesamiento en tiempo real. El campo de la Computación de Alto Rendimiento basado en elementos hardware de bajo coste es el puente necesario entre los problemas de computación y los sistemas multimedia que dan lugar a aplicaciones de usuario. En este sentido, la presente tesis va un paso más allá en el desarrollo de estos sistemas mediante el uso de la potencia de cálculo de las Unidades de Procesamiento Gráfico (GPU) en aplicaciones de propósito general. Con ello, aprovechamos la inherente capacidad de paralelización que poseen las GPU para procesar señales de audio y obtener aplicaciones de audio multicanal. El aumento de la capacidad computacional de los dispositivos de procesado ha estado vinculado históricamente al número de transistores que había en un chip. Sin embargo, hoy en día, las mejoras en la capacidad computacional se dan principalmente por el aumento del número de unidades de procesado y su uso para el procesado en paralelo. Las GPUs son un ejemplo muy representativo. Hoy en día, las GPUs poseen hasta miles de núcleos de computación. Tradicionalmente, las GPUs se han utilizado para el procesado de gráficos o imágenes. Sin embargo, la aparición de entornos sencillos de programación GPU, como por ejemplo CUDA, han permitido el uso de las GPU para aplicaciones de procesado general. De ese modo, el uso de las GPU se ha extendido a una amplia variedad de aplicaciones que requieren cálculo intensivo. Entre esta gama de aplicaciones, se incluye el procesado de señales de audio. No obstante, las transferencias de datos entre la CPU y la GPU y viceversa pusieron en duda la viabilidad de las GPUs para aplicaciones de audio en las que se requiere una interacción en tiempo real entre micrófonos y altavoces. Este es el caso de las aplicaciones basadas en filtrado adaptativo, donde el uso eficiente de la computación en paralelo no es sencillo. Por estas razones, hasta el comienzo de esta tesis, había muy pocas publicaciones que utilizaran la GPU para implementaciones en tiempo real de aplicaciones acústicas basadas en filtrado adaptativo. A pesar de todo, esta tesis pretende demostrar que las GPU son herramientas totalmente válidas para llevar a cabo aplicaciones de audio basadas en filtrado adaptativo que requieran elevados recursos computacionales. Con este fin, la presente tesis ha estudiado y desarrollado varias aplicaciones adaptativas de procesado de audio utilizando una GPU como procesador. Además, también analiza y resuelve las posibles limitaciones de cada aplicación tanto desde el punto de vista acústico como desde el punto de vista computacional. / [CAT] El camp del processament de senyals d'àudio ha experimentat un desenvolupament important als últims anys. Tant el mercat de consum com el professional segueixen mostrant un creixement en aplicacions d'àudio, com ara: els sistemes d'àudio immersiu que ofereixen una experiència de so òptima, els sistemes intel·ligents de reducció de soroll en els cotxes o les millores en sistemes de teleconferència o en audiòfons. El desenvolupament d'aquestes aplicacions té un propòsit comú d'augmentar o millorar el nombre de canals d'àudio, la pròpia qualitat de l'àudio o la sofisticació dels algorismes que s'utilitzen. Això, sovint dóna lloc a sistemes d'alt cost computacional, fins i tot quan es fan servir algorismes comuns de processat de senyal. Això es deu principalment al fet que els algorismes se solen aplicar a sistemes multicanals amb requeriments de processat en temps real. El camp de la Computació d'Alt Rendiment basat en elements hardware de baix cost és el pont necessari entre els problemes de computació i els sistemes multimèdia que donen lloc a aplicacions d'usuari. En aquest sentit, aquesta tesi va un pas més enllà en el desenvolupament d'aquests sistemes mitjançant l'ús de la potència de càlcul de les Unitats de Processament Gràfic (GPU) en aplicacions de propòsit general. Amb això, s'aprofita la inherent capacitat de paral·lelització que posseeixen les GPUs per processar senyals d'àudio i obtenir aplicacions d'àudio multicanal. L'augment de la capacitat computacional dels dispositius de processat ha estat històricament vinculada al nombre de transistors que hi havia en un xip. No obstant, avui en dia, les millores en la capacitat computacional es donen principalment per l'augment del nombre d'unitats de processat i el seu ús per al processament en paral·lel. Un exemple molt representatiu són les GPU, que avui en dia posseeixen milers de nuclis de computació. Tradicionalment, les GPUs s'han utilitzat per al processat de gràfics o imatges. No obstant, l'aparició d'entorns senzills de programació de la GPU com és CUDA, han permès l'ús de les GPUs per a aplicacions de processat general. D'aquesta manera, l'ús de les GPUs s'ha estès a una àmplia varietat d'aplicacions que requereixen càlcul intensiu. Entre aquesta gamma d'aplicacions, s'inclou el processat de senyals d'àudio. No obstant, les transferències de dades entre la CPU i la GPU i viceversa van posar en dubte la viabilitat de les GPUs per a aplicacions d'àudio en què es requereix la interacció en temps real de micròfons i altaveus. Aquest és el cas de les aplicacions basades en filtrat adaptatiu, on l'ús eficient de la computació en paral·lel no és senzilla. Per aquestes raons, fins al començament d'aquesta tesi, hi havia molt poques publicacions que utilitzessin la GPU per implementar en temps real aplicacions acústiques basades en filtrat adaptatiu. Malgrat tot, aquesta tesi pretén demostrar que les GPU són eines totalment vàlides per dur a terme aplicacions d'àudio basades en filtrat adaptatiu que requereixen alts recursos computacionals. Amb aquesta finalitat, en la present tesi s'han estudiat i desenvolupat diverses aplicacions adaptatives de processament d'àudio utilitzant una GPU com a processador. A més, aquest manuscrit també analitza i resol les possibles limitacions de cada aplicació, tant des del punt de vista acústic, com des del punt de vista computacional. / Lorente Giner, J. (2015). Adaptive signal processing for multichannel sound using high performance computing [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/58427 / TESIS