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

Adaptive Algorithms Design for Active Noise Control Systems with Disturbance at Reference and Error Microphones

Active noise control (ANC) is a popular choice for mitigating the acoustic noise in the surrounding environment resulting from industrial and medical equipment, appliances, and consumer electronics. ANC cancels the low frequency acoustic noise by generating a cancelling sound from speakers. The speakers are triggered by noise control filters and produce sound waves with the same amplitude and inverted phase to the original sound. Noise control filters are updated by adaptive algorithms. Successful applications of this technology are available in headsets, earplugs, propeller aircraft, cars and mobile phones. Since multiple applications are running simultaneously, efficiency of the adaptive control algorithms in terms of implementation, computations and performance is critical to the performance of the ANC systems. The focus of the present project is on the development of efficient adaptive algorithms that perform optimally in different configurations of ANC systems suitable for real world applications.Thesis (Ph.D.) -- University of Adelaide, School of Electrical & Electronic Engineering, 202

Active Control of Pressure Pulsation in a Switched Inertance Hydraulic System

The nature of digital hydraulic systems may cause pressure pulsation problems. For example, switched inertance hydraulic systems (SIHS), which are applied to adjust or control flow and pressure by a means that does not rely on dissipation of power, have noise problems due to the pulsed nature of the flow. An effective method to reduce the pulsation is important to improve system performance and increase efficiency. Although passive systems to reduce the noise have been shown to be effective in many situations, their attenuation frequency range is limited and they may be bulky. Furthermore, attenuation devices based on expansion chambers, accumulators or hoses are likely to be unsuitable for SIHS as they add compliance to the system and would impair the dynamic response. This thesis is concerned with issues relating to the development of an active noise canceller for attenuating the pressure pulsation which is caused primarily by pulsed flow from high-speed valves in SIHS. Active control methods are widely and successfully applied in the area of structureborne noise (SBN) and air-borne noise (ABN) cancellation. The idea is using the intentional superposition of waves to create a destructive interference pattern such that a reduction of the unwanted noise occurs. However, applications for fluid-borne noise (FBN) attenuation based on the ‘Active noise control (ANC) principle’ are rare due to the restriction of the hardware and experimental apparatus in previous researches. In this thesis, an adaptive controller has been developed for active control of pressure pulsation in hydraulic system. The principle of the adaptive LMS filter and details of the controller design are described and the implementation was carried out through simulation. The designed controller was applied on a vibration test rig initially prior to the hydraulic testing in order to investigate its advantages and limitations in practice. Extensive testing on a switched inertance hydraulic rig proved that the controller, which used a piezoelectric valve with fast response and good bandwidth, is effective and that it has several advantages over previous methods, being effective for low frequency cancellation, with a quick response, and is robust and versatile. A novel method for the accurate measurement of unsteady flowrate in a pipe was proposed. This was applied and validated on a pipe, and was shown to give good results. This method solves the difficulty for measuring the unsteady flowrate currently by using easy-measured signals, such as pressures. It can be used widely for predicting the unsteady flowrate along the pipe.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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

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

Reducing noise from wind turbines using active noise control.

M. Sc. Eng. University of KwaZulu-Natal, Durban 2014.Wind turbines while operating produce noise from the rotating mechanical parts and from the interaction of the blades with surrounding airflow. The noise produced by the blades consists of low frequency noise, airfoil self-noise and inflow turbulence noise. Active Noise Control (ANC) however, is a technique known to produce high level of attenuation in the low frequency range. The question therefore arose whether ANC can be used to reduce noise on wind turbines. The MATLAB simulation investigated the primary objective which was to introduce an opposite phase that is generated and combined with the primary “anti-noise” wave through an appropriate array of secondary noise, developed using a set of adaptive algorithms which consequently results in cancellation of both noises. The MATLAB simulation also investigated three secondary objectives: (i) to use filtered-x least mean squared (FXLMS) feed-forward ANC; (ii) to use a Finite Impulse Response (FIR) adaptive filter structure; and (iii) to minimize residual noise which consequently leads to reduction in low frequency aerodynamic noise from wind turbines. Field measurement was carried out in order to achieve one secondary objective: (i) to measure noise emission from a test turbine facility. Noise emission measurements were carried out at periods with the highest wind speeds which were between 10:00 am and 5:00 pm. Results show a reduction in sound pressure with increase in distance, with 64dBA at the foot of the tower and a sound pressure level of 54dBA at 30m away from the foot of the turbine. One-third octave analysis results indicate that although sound is attenuated with increasing distance, low frequency noise has higher frequency components having a value of 257Hz and a band power of 46dBA. Active Noise Control Simulations using FXLMS algorithm was carried out using sampled noise at 22050Hz and for 2 seconds and combining the noise signal, the FXLMS filter and the primary path filter. The FIR filter was used for the primary propagation path and a reduction of noise by 29dB has been achieved