Virtual sensors for local, three dimensional, broadband multiple-channel active noise control and the effects on the quiet zones

In this paper, two state of the art virtual sensor algorithms, i.e. the Remote Microphone Technique (RMT) and the Kalman filter based Virtual Sensing algorithm (KVS) are compared, in both state space (SS) and finite impulse response (FIR) implementations. The comparison focuses on the accuracy of the estimated sound pressure signals at the virtual locations and is based on actual measurements in a practical situation. The FIR implementation of the RMT algorithm was found to produce the most reliable results. It is implemented in a local, three dimensional, real-time, multiple-channel, broadband active noise control system. With this implementation, the benefits and limitations of the RMT-ANC system on the shape and size of the quiet zones are investigated

Multistage adaptive noise cancellation and multi-dimensional signal processing for ultrasonic nondestructive evaluation

Ultrasonic signal processing presents several challenges with respect to both noise removal and interpretation. The interference of unwanted reflections from material grain structure can render the data extremely noisy and mask the detection of small flaws. It is therefore imperative to separate the flaw reflections from grain noise. The interpretation or classification of ultrasonic signals in general is relatively difficult due to the complexity of the physical process and similarity of signals from various classes of reflectors;Adaptive noise cancellation techniques are ideally suited for reducing spatially varying noise due to the grain structure of material in ultrasonic nondestructive evaluation. In this research, a multi-stage adaptive noise cancellation (MANC) scheme is proposed for reducing spatially varying grain noise and enhancing flaw detection in ultrasonic signals. The overall scheme is based on the use of an adaptive least mean square error (LMSE) filter with primary and reference signals derived from two adjacent positions of the transducers. Since grain noise is generally uncorrelated, in contrast to the correlated flaw echoes, adaptive filtering algorithms exploit the correlation properties of signals in a C-scan image to enhance the signal-to-noise ratio (SNR) of the output signal;A neural network-based signal classification system is proposed for the interpretation of ultrasonic signals obtained from inspection of welds, where signals have to be classified as resulting from porosity, slag, lack of fusion, or cracks in the weld region. Standard techniques rely on differences in individual A-scans to classify the signals. This thesis investigates the need for investigating signal features that incorporate the effects of beam spread and echo dynamics. Such effects call for data interpretation schemes that include a neighborhood of A-scans carrying information about a reflector. Several ultrasonic signal features based on the information in a two-dimensional array of ultrasonic waveforms, ranging from the estimation of statistical characteristics of signals to two and three-dimensional transform-based methods, are evaluated. A two-dimensional scan of ultrasonic testing is also represented in the form of images (B- and B\u27-scans). Multidimensional signal and image-processing algorithms are used to analyze the images. Two and three-dimensional Fourier transforms are applied to ultrasonic data that are inherently three-dimensional in nature (2 spatial and 1 time). A variety of transform-based features are then utilized for obtaining the final classification

ACTIVE NOISE CONTROL USING CARBON NANOTUBE THERMOPHONES: CASE STUDY FOR AN AUTOMOTIVE HVAC APPLICATION

The goal of this project was to reduce the overall noise levels emitted by the HVAC components in a vehicle’s cabin. More specifically, the feasibility of achieving this goal using two key technologies was investigated. The first of these technologies, Active Noise Control (ANC), is a noise attenuation technique that relies on destructive interference that “cancels” unwanted noise. Typically used in situations where physical constraints prevent passive attenuation techniques from being used, ANC is known for its high size-to-effectiveness ratio. This benefit cannot be gained without a cost however; the complexity of ANC systems is significantly higher than their passive counterparts. This is due to the signal processing and actuator designs required. These actuators often take the form of moving-coil loudspeakers which, while effective, are often bulky. Because of this they are difficult to “drop in” to an existing system. This is where the second technology comes in. Carbon Nanotube (CNT) Thermophones are solid-state speakers that operate by using rapid heat fluctuations to create sound. Called the “thermoacoustic effect,” (TE) the theory of this operating principle dates to the turn of the 20th century. Useful demonstration of TE did not occur until 2008, however, when researchers first developed the first CNT thermophones. The hallmark characteristics of these transducers are their small size and flexible nature. Compared to traditional loudspeakers they have a much smaller form factor and are more versatile in terms of where they can be placed in a cramped system. The marriage of CNT transducers to ANC technology shows promise in improving the application space and ease of installation of ANC systems. Getting these two to cooperate, however, is not without challenges. A case study for this union is presented here; the application space being the ducted environment of vehicle HVAC systems

Prediction & Active Control of Multi-Rotor Noise

Significant developments have been made in designing and implementation of Advanced Air Mobility Vehicles (AAMV). However, wider applications in urban areas require addressing several challenges, such as safety and quietness. These vehicles differ from conventional helicopter in that they operate at a relatively lower Reynolds number. More chiefly, they operate with multiples of rotors, which may pose some issues aerodynamically, as well as acoustically. The aim of this research is to first investigate the various noise sources in multi-rotor systems. High-fidelity simulations of two in-line counter-rotating propellers in hover, and in forward flight conditions are performed. Near field flow and acoustic properties were resolved using Hybrid LES-Unsteady RANS approach. Far-field sound predictions were performed using Ffowcs-Williams-Hawkings formulation. The two-propeller results in hovering are compared with that of the single propeller. This enabled us to identify the aerodynamic changes resulting from the proximity of the two propellers to each other and to understand the mechanisms causing the changes in the radiated sound. It was discovered that there is a dip in the thrust due to the relative proximity of the rotors. Owing to this, there is also some acoustic banding above the rotors mainly because they operate at the same rotational rate. We then considered the forward flight case and compared it with the corresponding hovering case. This enabled us to identify the aerodynamic changes resulting from the incoming stream. By examining the near acoustic field, the far-field spectra, the Spectral Proper Orthogonal Decomposition, and by conducting periodic averaging, we were able to identify the sources of the changes to the observed tonal and broadband noise. The convection of the oncoming flow was seen to partially explain the observed enhancement in the tonal and BBN, compared to the hovering case. It is well known that High fidelity methods are critical in predicting the full spectrum of rotor acoustics. However, these methods can be prohibitively expensive. We present here an investigation of the feasibility of reduction methods such as Proper Orthogonal Decomposition as well as Dynamic Mode decomposition for reduction of data obtained via Hybrid Large-Eddy – Unsteady Reynolds Averaged Navier Stokes approach (HLES) to be used further to obtain additional parameters. Specifically, we investigate how accurate reduced models of the high-fidelity computations can be used to predict the far-field noise. It was found that POD was capable of reconstructing accurately the parameters of interest with 15-40% of the total mode energies, whereas the DMD could only reconstruct primitive parameters such as velocity and pressure loosely. A rank truncation convergence criterion \u3e 99.8% was needed for better performance of the DMD algorithm. In the far-field spectra, DMD could only predict the tonal contents in the lower- mid frequencies whiles the POD could reproduce all frequencies of interest. Lastly, we develop an active rotor noise control technology to reduce the in-plane thickness noise associated with multi-rotor Advanced Air Mobility Vehicles (AAMV). An actuation signal is determined via the Ffowcs-Williams-Hawking (FWH) formula. Two in-line rotors are considered and we showed that the FWH-determined actuation signal can produce perfect cancellation at a point target. However, the practical need is to achieve noise reduction over an azimuthal zone, not just a single point. To achieve this zonal noise reduction, an optimization technique is developed to determine the required actuation signal produced by the on-blade distribution of embedded actuators on the two rotors. For the specific geometry considered here, this produced about 9 dB reduction in the in-plane thickness noise during forward flight of the two rotors. We further developed a technology that replaces using a point actuator on each bladed by distributed micro actuators system to achieve the same noise reduction goal with significantly reduced loading amplitudes per actuator. Overall, this research deepens the knowledge base of multi-rotor interaction. We utilize several techniques for extracting various flow and acoustic features that help understand the dynamics of such systems. Additionally, we provide a more practical approach to active rotor noise control without a performance penalty to the rotor system

Aircraft interior noise reduction by alternate resonance tuning

The focus is on a noise control method which considers aircraft fuselages lined with panels alternately tuned to frequencies above and below the frequency that must be attenuated. An interior noise reduction called alternate resonance tuning (ART) is described both theoretically and experimentally. Problems dealing with tuning single paneled wall structures for optimum noise reduction using the ART methodology are presented, and three theoretical problems are analyzed. The first analysis is a three dimensional, full acoustic solution for tuning a panel wall composed of repeating sections with four different panel tunings within that section, where the panels are modeled as idealized spring-mass-damper systems. The second analysis is a two dimensional, full acoustic solution for a panel geometry influenced by the effect of a propagating external pressure field such as that which might be associated with propeller passage by a fuselage. To reduce the analysis complexity, idealized spring-mass-damper panels are again employed. The final theoretical analysis presents the general four panel problem with real panel sections, where the effect of higher structural modes is discussed. Results from an experimental program highlight real applications of the ART concept and show the effectiveness of the tuning on real structures

Multibeam volume acoustic backscatter imagery and reverberation measurements in the Northeastern Gulf of Mexico

Multibeam volume acoustic backscatterimagery and reverberation measurements are derived from data collected in 200-m-deep waters in the northeastern Gulf of Mexico, with the Toroidal Volume Search Sonar (TVSS), a 68-kHz cylindrical sonar operated by the U.S. Navy’s Coastal System Station. The TVSS’s 360-degree vertical imaging plane allows simultaneous identification of multiple volume scattering sources and their discrimination from backscatter at the sea surface or the seafloor. This imaging capability is used to construct a three-dimensional representation of a pelagic fish school near the bottom. Scattering layers imaged in the mixed layer and upper thermocline are attributed to assemblages of epipelagic zooplankton. The fine scale patchiness of these scatterers is assessed with the two-dimensional variance spectra of vertical volume scattering strength images in the upper and middle water column. Mean volume reverberation levels exhibit a vertical directionality which is attributed to the volume scattering layers. Boundary echo sidelobe interference and reverberation is shown to be the major limitation in obtaining bioacoustic data with the TVSS. Because net tow and trawl samples were not collected with the acoustic data, the analysis presented is based upon comparison to previous biologic surveys in the northeastern Gulf of Mexico and reference to the bioacoustic literature