scholarly journals Combination of Robust Algorithm and Head-Tracking for a Feedforward Active Headrest

2019 ◽  
Vol 9 (9) ◽  
pp. 1760 ◽  
Author(s):  
Rong Han ◽  
Ming Wu ◽  
Chen Gong ◽  
Shangshuai Jia ◽  
Tieli Han ◽  
...  
Keyword(s):  
High Speed ◽  
Noise Control ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Head Movements ◽  
Frequency Noise ◽  
Head Tracking ◽  
High Speed Train ◽  
Robust Algorithm ◽  
Active Noise

Active headrest can reduce the low-frequency noise around ears based on the principle of active noise control. This paper presents a combination of robust algorithm and head-tracking for a feedforward active headrest to reduce the broadband noise for a sleeper on a high-speed train. A robust algorithm based on the feedforward active noise control is proposed to improve the noise control performance during head rotations. The head-tracking system with infrared rangefinders tracks the head position based on the Kalman filter to further improve system performance with head movements. Experiments were conducted on a model of a sleeper on a high-speed train. The experimental results show that the proposed active headrest system effectively controls broadband noise with head movements and rotations.

scholarly journals Ultra-broadband local active noise control with remote acoustic sensing

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tong Xiao ◽  
Xiaojun Qiu ◽  
Benjamin Halkon
Keyword(s):  
Acoustic Signal ◽  
Noise Control ◽  
Tracking System ◽  
Active Noise Control ◽  
Laser Doppler Vibrometer ◽  
Head Movements ◽  
Head Tracking ◽  
Acoustic Sensing ◽  
Minimal Invasiveness ◽  
Active Noise

AbstractOne enduring challenge for controlling high frequency sound in local active noise control (ANC) systems is to obtain the acoustic signal at the specific location to be controlled. In some applications such as in ANC headrest systems, it is not practical to install error microphones in a person’s ears to provide the user a quiet or optimally acoustically controlled environment. Many virtual error sensing approaches have been proposed to estimate the acoustic signal remotely with the current state-of-the-art method using an array of four microphones and a head tracking system to yield sound reduction up to 1 kHz for a single sound source. In the work reported in this paper, a novel approach of incorporating remote acoustic sensing using a laser Doppler vibrometer into an ANC headrest system is investigated. In this “virtual ANC headphone” system, a lightweight retro-reflective membrane pick-up is mounted in each synthetic ear of a head and torso simulator to determine the sound in the ear in real-time with minimal invasiveness. The membrane design and the effects of its location on the system performance are explored, the noise spectra in the ears without and with ANC for a variety of relevant primary sound fields are reported, and the performance of the system during head movements is demonstrated. The test results show that at least 10 dB sound attenuation can be realised in the ears over an extended frequency range (from 500 Hz to 6 kHz) under a complex sound field and for several common types of synthesised environmental noise, even in the presence of head motion.

scholarly journals Multichannel Feedforward Active Noise Control System with Optimal Reference Microphone SelectorBased on Time Difference of Arrival

2018 ◽  
Vol 8 (11) ◽  
pp. 2291 ◽  
Author(s):  
Kenta Iwai ◽  
Satoru Hase ◽  
Yoshinobu Kajikawa
Keyword(s):  
Noise Control ◽  
Acoustic Noise ◽  
Control Point ◽  
Active Noise Control ◽  
Broadband Noise ◽  
Time Difference ◽  
Arrival Direction ◽  
Noise Sources ◽  
Time Difference Of Arrival ◽  
Active Noise

In this paper, we propose a multichannel active noise control (ANC) system with an optimal reference microphone selector based on the time difference of arrival (TDOA). A multichannel feedforward ANC system using upstream reference signals can reduce various noises such as broadband noise by arranging reference microphones close to noise sources. However, the noise reduction performance of an ANC system degrades when the noise environment changes, such as the arrival direction. This is because some reference microphones do not satisfy the causality constraint that the unwanted noise propagates to the control point faster than the anti-noise used to cancel the unwanted noise. To solve this problem, we propose a multichannel ANC system with an optimal reference microphone selector. This selector chooses the reference microphones that satisfy the causality constraint based on the TDOA. Some experimental results demonstrate that the proposed system can choose the optimal reference microphones and effectively reduce unwanted acoustic noise.

Improvement of noise reduction performance for a high-speed elevator using modified active noise control

2014 ◽  
Vol 79 ◽  
pp. 58-68 ◽  
Author(s):  
In-Hyung Yang ◽  
Jae-Eun Jeong ◽  
Un-Chang Jeong ◽  
Jin-Su Kim ◽  
Jae-Eung Oh
Keyword(s):  
Noise Reduction ◽  
High Speed ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise

KTX Interior-Noise Reduction Performance Comparison Using Multichannel Active-Noise Control

2012 ◽  
Vol 152-154 ◽  
pp. 1891-1898
Author(s):  
Hyeon Seok Jang ◽  
Young Min Kim ◽  
Saehan Kim ◽  
Taeoh Lee ◽  
Kwon Soon Lee
Keyword(s):  
Noise Reduction ◽  
High Speed ◽  
Noise Control ◽  
Active Noise Control ◽  
Sound Field ◽  
Performance Comparison ◽  
High Speed Rail ◽  
Active Noise ◽  
Tunnel Section ◽  
Fxlms Algorithm

In many countries, the use of the KTX high-speed rail has been generalized of late. Therefore, its customers who initially pursued only convenience and speed have begun pursuing quality services such as comfort and stability. Thus, the importance of reducing the noise in the high-speed rail is increasing. The active noise is best choice to reduce noise because of being able to actively reduce the ambient noise coming from the environmental-factor changes. But it’s too hard in a three-dimensional closed-space sound field such as the interior of a high-speed rail. In this study, we used multichannel(2x2) FXLMS algorithm for applying ANC system in KTX. In detail, after measuring the noise inside KTX during its runs in South Korea, multichannel active noise control was simulated to determine the extent to which it can reduce the noise inside KTX. Simulation was done using a multichannel FXLMS algorithm for reducing the actual noise inside KTX and the noise reduction in the open-space section of KTX was compared with that in the tunnel section, and the active-noise-control performances in the low-frequency (below 500 Hz) region were compared.

Active Noise Control Using Multi-Layered Perceptron Neural Networks

1997 ◽  
Vol 16 (2) ◽  
pp. 109-144 ◽  
Author(s):  
M.O. Tokhi ◽  
R. Wood
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Noise Control ◽  
Learning Algorithm ◽  
Free Field ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Broadband Noise ◽  
Active Noise

This paper presents the development of a neuro-adaptive active noise control (ANC) system. Multi-layered perceptron neural networks with a backpropagation learning algorithm are considered in both the modelling and control contexts. The capabilities of the neural network in modelling dynamical systems are investigated. A feedforward ANC structure is considered for optimum cancellation of broadband noise in a three-dimensional propagation medium. An on-line adaptation and training mechanism allowing a neural network architecture to characterise the optimal controller within the ANC system is developed. The neuro-adaptive ANC algorithm thus developed is implemented within a free-field environment and simulation results verifying its performance are presented and discussed.

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