An array virtual extension method for power equipment acoustic emission direction of arrival estimation based on high‐order cumulants

Abstract

Abstract The performance of array‐based power equipment acoustic emission (AE) source directional of arrival (DOA) estimation methods is decided by not only algorithm performance, but also the array hardware parameters, that is, array aperture, sensor number, and so forth. Improving the estimation performance by hardware approaches always leads to the increase in cost. In this study, an array virtual extension method based on high‐order cumulants is proposed which can improve the sensor array performance without the need for hardware change or extra investment. Compared to low‐order cumulants, the high‐order cumulants established from Taylor expansion contain higher order terms which are omitted in low order cumulants. Therefore, they have more detailed directional information about the signal source to improve the DOA estimation performance. Moreover, because high‐order cumulants contain information only for the non‐Gaussian components, the array after extension shows better anti‐Gaussian noise performance. Depending on the establishment method of the high‐order cumulant, two types of extension including aperture extension and sensor number extension are proposed for different application scenarios. Simulation and field tests results show that the array directional resolution is improved around 40% by aperture extension and the spectrum sidelobe level is reduced about 14 dB by sensor extension.

Keywords

• acoustic emission
• acoustic signal processing
• array signal processing
• direction‐of‐arrival estimation
• Gaussian noise
• higher order statistics