Properties of the Far-Field Pressure Signatures of Individual Jet Noise Sources

Abstract

The detection of intermittent near-field noise sources is achieved by continuous wavelet transform of far-field acoustic data. The similarities between signals from three far-field microphones in the annular cone of acoustic radiation from coherent sources in a Ma = 0.6 cold jet are used to identify some of the loudest events. Cross-correlation of relevant band-passed excerpts identifies the most reliable matches, which occur at the rate of one every 20 dimensionless time units on average, and are intermittent in both time and frequency with no obvious pattern. Processing our database produced a catalog of over 9500 individual events with quantitative properties including the magnitude, frequency and time of detection at each microphone. The differences in detection times (lags) are distributed smoothly around the peak of cross-correlations for the raw data. We show how source magnitude and frequency depends on lags, and relate the lags to their relative source location.

Time-Domain Analysis of Excited Subsonic Jet Noise

“…While spectral analysis is the standard tool of jet noise research, there is some precedent in the literature for jet noise analysis assuming a fundamentally intermittent signals [39][40][41][42][43][44][45]. A common tool used in these works is wavelet analysis -the underlying principle of which is that the signals under examination cannot be adequately described by a set of periodic waves.…”

“…Results to date have mainly focused on the relationship of the resulting directivity patterns to wave-packet models for jet noise. A group at Syracuse University [45,53] used wavelet filtering and correlation on both near and far-field to determine how the near-field events are related to the far-field events. Some of their work is still preliminary, but warrants mentioning as a significant attempt to trace the intermittent aspects of jet noise back toward their sources.…”

Directivity and intermittency in the nearfield of a Mach 1.3 jet

“…15,16 Other techniques employed to connect the near- and farfields include the wavelet approach as discussed in Lewalle et al. 17…”

Investigation of the benefits of unsteady blowing actuation on a 2D wind turbine blade

“…For wavelet terminology, proofs and alternative scaling, see [11,12]. Here, we adopt a scaling that simplifies the formulae and facilitates the connection between Gaussian filter scale, Morlet frequency and Fourier frequency [12,13]. The purpose of this present study is twofold: (1) demonstrate a simple closed-loop flow control system for a two-dimensional (2D) wind turbine airfoil with leading-edge unsteady blowing, surface pressure sensors and a computer program-based controller; and (2) analyze the unsteady separated flow on the airfoil induced by the upstream cylinder using wavelets.…”