Global feedforward active noise control using a linearly constrained loudspeaker beamformer and a sensor interpolation approach
Time: 7:00 am
Author: Yicheng Hsu
Abstract ID: 1472
The key issue of three-dimensional active noise control (3D ANC) problems is that global control is generally difficult, given limited number of discrete sensors. In this paper, feedforward multi-channel ANC approach is proposed to circumvent this difficulty. In view of the model-matching principle and multiple secondary sources, an underdetermined multi-channel inverse filtering (UMIF) system is formulated. With this UMIF system as a design constraint, a cost function is introduced to minimize the noise energy at a large number of control points. This linearly constrained minimum variance (LCMV) proves effective in broadening the controlled area in a 3D space. Optimal deployment of control points and the regularization terms of LCMV approach are also examined. To implement the proposed ANC system in a non-freefield environment, sensor interpolation can be used to find the frequency response between control points and loudspeakers, with plane wave decomposition and some room response measurements. The proposed ANC system has been implemented on a six-element linear loudspeaker array. Simulation and experiment results have demonstrated that the propose approach has yielded significant noise reduction performance in a large control area.
Determination of tonal signal parameters based on zero crossing detection
Time: 3:00 pm
Author: Michal Luczynski
Abstract ID: 1950
This paper presents a method for identifying tonal signal parameters using zero crossing detection. The signal parameters: frequency, amplitude and phase can change slowly in time. The described method allows to obtain accurate detection using possibly small number of signal samples. The detection algorithm consists of the following steps: frequency filtering, zero crossing detection and parameter reading. Filtering of the input signal is aimed at obtaining a signal consisting of a single tonal component. Zero crossing detection allows the elimination of multiple random zero crossings, which do not occur in a pure sine wave signal. The frequency is based on the frequency of transitions through zero, the amplitude is the largest value of the signal in the analysed time interval, and the initial phase is derived from the moment at which the transition through zero occurs. The obtained parameters were used to synthesise a compensation signal in an active tonal component reduction algorithm. The results of the algorithm confirmed the high efficiency of the method.
Active noise control without secondary path modeling: algorithm and implementation
Time: 7:40 pm
Author: Xing Ren
Abstract ID: 1995
Active noise control (ANC) has been intensively studied for decades. The most classical ANC algorithm should be the filtered-x least mean square (FxLMS) algorithm, which needs the model of the secondary path to work. Thus, the residual error of the ANC system is closely related to the preciseness of the secondary path model. In many applications, the secondary path is often time-varying. Therefore, off-line identification of the secondary path is not applicable. However, on-line identification often requires an additional white noise as a stimulating signal of the secondary path, which will deteriorate the final noise reduction effect. This paper proposes an improved artificial bee colony (ABC) algorithm for ANC system, which does not require identification of the secondary path. In order to guarantee the convergence of the algorithm and accelerate the convergence speed, this paper introduces a variable forgetting factor into the fitness function, and improves the traditional ABC algorithm by integrating LMS algorithm into the ABC algorithm. A single channel ANC system equipped with an FPGA hardware platform is set up in an anechoic chamber, and experiments show that the proposed algorithm can produce a satisfactory noise reduction effect without modeling the secondary path.
Simulation of LMS based adaptive noise cancellation using Labview
Time: 2:20 pm
Author: Maja Anachkova
Abstract ID: 2128
The audio signals processed in the signal measurement systems are inevitably susceptible to unwanted noise which significantly affects the quality of the signal and the overall performance of the signal communication systems. Due to its random and unpredictable nature, the amount of noise in signals has proven to be a significant issue in designing these systems and recently has been a trending research topic. In this regard, the active noise cancellation method has proven to be an effective technique for eliminating the noise effects on signal processing. The concept of active noise cancellation is based on the application of adaptive filters and algorithms proposed to reduce the signal corruption and distortion caused by the noise due to the principle of destructive interference. In this paper a simulation model of active noise reduction technique using the LMS (Least Mean Square) algorithm in Labview is presented. The purpose of the work is to investigate the noise cancellation effect on a recorded audio file in terms of analyzing the audio file before and after filtering out the noise by using the LMS algorithm and discuss the results thereof.
Active noise control for open windows
Time: 7:20 am
Author: Shahin Sohrabi
Abstract ID: 2306
Over the last decades, the applications of the active noise control system are broadened. In this study, the active noise control is modeled to reduce the noise pass through an open window. The objective is to define a suitable location for the control sources and error microphones to achieve more noise level reduction at the other side of the window. The performances of the active noise control system are calculated for two different arrangements: (1) the control sources on the edge of the opening and (2) the control sources distributed on the surface of the window. Furthermore, two cost functions are considered to model the noise control system including the minimization of the total squared pressure at cancellation points and the minimization of sound intensity at the surface of the aperture.
A compact active structural acoustic control method for minimizing radiated sound power
Time: 7:40 am
Author: Scott Sommerfeldt
Abstract ID: 2393
Active structural acoustic control is an active control method that controls a vibrating structure in a manner that reduces the sound power radiated from the structure. Such methods focus on attenuating some metric that results in attenuated sound power, while not necessarily minimizing the structural vibration. The work reported here outlines the weighted sum of spatial gradients (WSSG) control metric as a method to attenuate structural radiation. The WSSG method utilizes a compact error sensor that is able to measure the acceleration and the acceleration gradients at the sensor location. These vibration signals are combined into the WSSG metric in a manner that is closely related to the radiated sound power, such that minimizing the WSSG also results in a minimization of the sound power. The connection between WSSG and acoustic radiation modes will be highlighted. Computational and experimental results for both flat plates and cylindrical shells will be presented, indicating that the WSSG method can achieve near optimal attenuation of the radiated sound power with a minimum number of sensors.
Semi-adaptive active noise cancellation headphones
Time: 2:00 pm
Author: Song Li
Abstract ID: 2808
Active noise cancellation (ANC) headphones are becoming increasingly important as they can effectively attenuate perceived ambient noise. Fixed filters are commonly applied in commercially available ANC headphones due to their robustness. However, they are not capable of adapting to changes that occur in dynamic environments, resulting in degraded ANC performance. In contrast, adaptive filters are able to update the ANC filters to compensate for noise in dynamic environments, but large estimation errors can occur due to a sudden change in direction/type of noise or secondary path. Some studies have suggested an ANC system by combining fixed and adaptive filters. Based on this mechanism, we propose a semi-adaptive ANC system in which the fixed and adaptive filters are weighted in real-time. Initially, the weighting for the fixed filter dominates the whole system to ensure the robustness of the ANC system. Then, the residual error provided by the adaptive filter is simulated and compared to the real measured one to determine the relative weighting between the fixed and adaptive filters. In this study, this approach is applied to a feedback ANC system. Simulation results show that our proposed approach achieves high noise attenuation performance while maintaining robustness with time-varying secondary paths.
Multi-channel feedforward active noise control system for reducing snore noise with snore noise-term detection
Time: 6:40 am
Author: Koki Nakamura
Abstract ID: 1755
In this paper, a multi-channel feedforward active noise control system for reducing snore noise with noise-term detection is proposed. The snore noise consists of a noise-term and a silent-term, and it is difficult to reduce the snore noise by the active noise control system. Since the conventional multi-channel feedforward active noise control system updates the noise control filters even in the silent-term, the conventional active noise control system updates the noise control filters unnecessarily. Therefore, the proposed multi-channel feedforward active noise control system introduces threshold processing to update the noise control filters only in the noise-term. Owing to this process, it is possible to reduce the update count of the noise control filters. Simulation results show that the proposed active noise control system can reduce the snore noise as same as the conventional active noise control system and can reduce the update count of the noise control filters compared to the conventional active noise control system.
Optimal ANC System Arrangement Based on Complete System Analyses Applying COSMOL Multiphysics and Matlab
Time: 6:00 am
Author: MIQING WANG
Abstract ID: 1824
In real active noise control system implementation, the arrangement of secondary sources and error microphones have significant effect on the performance of the system. Analytical and experimental ways are usually combined to determine the best system layout. In this paper, we use COSMOL Multiphysics to accurately model the acoustic environment in enclosures with the real measured dimensions and parameters. Matlab is adopted to simulate the basic active noise control algorithms. The combined simulation results are used to decide the optimal system layout of the real ANC system. Experiments are conducted on a real ANC system with EVAL-21489-EZLITE from ADI to validate the analyzed and simulation results.
Acoustic analysis of snoring sound from different microphones
Time: 6:20 am
Author: li ding
Abstract ID: 1962
Snoring is a common symptom of obstructive sleep apnea-hypopnea syndrome. The results show that there are obvious differences for most microphones in terms of the data distribution of features in the time and frequency domain. The results of snoring analysis from different recordings devices would be totally divergent. In view of this, when developing snoring analysis devices based user selected microphones (i.e. smartphone) recorded, we should take into account the discrepancy between different microphones.