Implementation of Microphone Array Processing Techniques on a Synthetic Array for Fluid Power Noise Diagnostics

Dan Ding, Purdue University

Abstract

Fluid power is widely used in a variety of applications such as construction machines, aerospace, automotive, agricultural machinery, manufacturing, etc. Although this technology has many obvious advantages such as compactness, robustness, high power density, and so forth, there is much room for improvement, of which one of the most important and challenging problems is the noise. Different institutes have been researching fluid power noise for decades. However, much of the experimental investigation was based on simple measurement and analysis techniques, which left the designers/researchers no method of understanding the complicated phenomena. A microphone array is a powerful tool that unfortunately has not been introduced to the fluid power noise research. By capturing the magnitude and phase information in space, a microphone array enables the noise source identification, separation, localization and so forth. This thesis focuses on implementing the microphone array processing techniques on a synthetic microphone array for fluid power noise diagnostics. Differing from traditional scan-based approaches, the synthetic array is created by synchronizing the non-synchronous measurements to achieve the equivalent effect of a multi-microphone snapshot. The final results will show the power of microphone arrays and provide an economical solution to achieve approximate results when a real microphone array is not available.

Degree

M.Sc.

Advisors

Bolton, Purdue University.

Subject Area

Design|Acoustics|Hydraulic engineering|Mathematics|Music|Robotics

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