Abstract
Original language  English 

Qualification  Licentiate Degree 
Awarding Institution 

Place of Publication  Espoo 
Publisher  
Print ISBNs  9789513874575 
Electronic ISBNs  9789513874582 
Publication status  Published  2012 
MoE publication type  G3 Licentiate thesis 
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Keywords
 active noise control
 active sound profiling
 commandFXLMS algorithm
 sinusoidal signal filtering
 adaptive leakage factor
Cite this
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Development of a robust and computationallyefficient active sound profiling algorithm in a passenger car : Licentiate thesis. / Kataja, Jari.
Espoo : VTT Technical Research Centre of Finland, 2012. 92 p.Research output: Thesis › Licenciate › Theses
TY  THES
T1  Development of a robust and computationallyefficient active sound profiling algorithm in a passenger car
T2  Licentiate thesis
AU  Kataja, Jari
N1  Project code: 77780
PY  2012
Y1  2012
N2  Active noise control is a technique to cancel unwanted sound using adjustable secondary sound. In active sound profiling, the target is to obtain a certain sound field or profile and the power over specific frequencies can be altered in a desired way, even by amplifying it. Active sound profiling can be used for increasing the sound quality in a passenger car, for example, by modifying the engine noise inside the car cabin. A fundamental algorithm in active sound profiling is the commandFXLMS (CFXLMS) algorithm, which is an extension of the famous FXLMS algorithm widely used in active noise control. The computational demand of the CFXLMS algorithm becomes excessive in multiplechannel systems with engine noise components to be controlled using several loudspeakers and microphones. The most timeconsuming part of the CFXLMS algorithm is the filtering of the reference signals. In order to reduce the computational burden, a new way to modify the reference signals in narrowband systems has been developed in this work. Instead of conventional filtering operations, the new method is based on delaying the sinusoidal reference signals and modifying their amplitude. The algorithm should work reliably and maintain stability in all operating points. In this work, an adaptive leakage has been developed for the CFXLMS algorithm to increase its robustness. The objective is to limit the adaptive filter coefficients at frequencies where the phase shift of the plant is large. Such phase shifts occur at resonances, for example, and the performance of the algorithm is drastically degraded. In this work, the CFXLMS algorithm has also been combined with the EEFXLMS algorithm so that frequencyindependent step sizes can be used. This increases robustness and enables faster tuning of the algorithm. The developed algorithm has been tested in a simulation model and in an experimental active sound profiling system installed in a car. The results prove that the algorithm works with sufficient accuracy. The convergence is fast and stability is maintained in all operating points.
AB  Active noise control is a technique to cancel unwanted sound using adjustable secondary sound. In active sound profiling, the target is to obtain a certain sound field or profile and the power over specific frequencies can be altered in a desired way, even by amplifying it. Active sound profiling can be used for increasing the sound quality in a passenger car, for example, by modifying the engine noise inside the car cabin. A fundamental algorithm in active sound profiling is the commandFXLMS (CFXLMS) algorithm, which is an extension of the famous FXLMS algorithm widely used in active noise control. The computational demand of the CFXLMS algorithm becomes excessive in multiplechannel systems with engine noise components to be controlled using several loudspeakers and microphones. The most timeconsuming part of the CFXLMS algorithm is the filtering of the reference signals. In order to reduce the computational burden, a new way to modify the reference signals in narrowband systems has been developed in this work. Instead of conventional filtering operations, the new method is based on delaying the sinusoidal reference signals and modifying their amplitude. The algorithm should work reliably and maintain stability in all operating points. In this work, an adaptive leakage has been developed for the CFXLMS algorithm to increase its robustness. The objective is to limit the adaptive filter coefficients at frequencies where the phase shift of the plant is large. Such phase shifts occur at resonances, for example, and the performance of the algorithm is drastically degraded. In this work, the CFXLMS algorithm has also been combined with the EEFXLMS algorithm so that frequencyindependent step sizes can be used. This increases robustness and enables faster tuning of the algorithm. The developed algorithm has been tested in a simulation model and in an experimental active sound profiling system installed in a car. The results prove that the algorithm works with sufficient accuracy. The convergence is fast and stability is maintained in all operating points.
KW  active noise control
KW  active sound profiling
KW  commandFXLMS algorithm
KW  sinusoidal signal filtering
KW  adaptive leakage factor
M3  Licenciate
SN  9789513874575
T3  VTT Science
PB  VTT Technical Research Centre of Finland
CY  Espoo
ER 