A Study of Sound Source Characteristics in Active Noise Control and Fault Diagnosis

Abstract

Active noise control (ANC) is an effective technique used to reduce noise levels at the controlled points by introducing a cancellation sound wave into the primary acoustic field. To achieve better sound design and noise attenuation, it is critical to have good knowledge of the characteristics of the primary noise source, which is also necessary for condition monitoring (CM). This paper investigates various ANC schemes to achieve both noise reduction and fault diagnosis. Firstly an effective acoustic measurement method is developed to estimate the characteristics of noise sources for the ANC in a pipeline system. Two sensors are mounted along the pipe to measure the acoustic signals and the source of the noise is estimated based on these measurements. An ANC algorithm embedded with CM capability is developed for both noise reduction and fault detection in the system. The algorithm is evaluated through both simulation study and experimental work. Preliminary results show that both noise reduction and fault diagnosis can be achieved and the system operates reliably under different operating conditions. Keywords: Active noise control, Condition monitoring, Diesel engine, Fault diagnosis