Capturing and Modeling a Three-Dimensional Stationary Noise Source Directivity Pattern with a Dynamic Array in the Near Field

The author has studied several legacy landmark methodologies to develop an original measurement technique. Spherical harmonics modeling practices were leveraged to accurately represent a source directivity pattern. In this thesis a lightweight microphone measurement array that was manually maneuvered around a static noise source was employed. The measurement technique consisted of inserting a head-tracker sensor onto the microphone array to allow the location of the captured acoustic Sound Pressure Level (SPL) to be investigated. By leveraging the historical methodologies the acoustic SPL and location data collected with this technique were processes to represent a directivity pattern of the compressor source chosen. The results indicated that the measurement technique is valid for capturing acoustic SPL and location data of a static noise source with a dynamic array. Propagation techniques yielded a ten decibel difference between the measured and predicated SPLs. The dynamic measurement technique and method for characterizing the three-dimensional acoustic directivity of a static noise source is further presented in this thesis

Scan and paint: theory and practice of a sound field visualization method

Sound visualization techniques have played a key role in the development of acoustics throughout history. The development of measurement apparatus and techniques for displaying sound and vibration phenomena has provided excellent tools for building understanding about specific problems. Traditional methods, such as step-by-step measurements or simultaneous multichannel systems, have a strong tradeoff between time requirements, flexibility, and cost. However, if the sound field can be assumed time stationary, scanning methods allow us to assess variations across space with a single transducer, as long as the position of the sensor is known. The proposed technique, Scan and Paint, is based on the acquisition of sound pressure and particle velocity by manually moving a P-U probe (pressure-particle velocity sensors) across a sound field whilst filming the event with a camera. The sensor position is extracted by applying automatic color tracking to each frame of the recorded video. It is then possible to visualize sound variations across the space in terms of sound pressure, particle velocity, or acoustic intensity. In this paper, not only the theoretical foundations of the method, but also its practical applications are explored such as scanning transfer path analysis, source radiation characterization, operational deflection shapes, virtual phased arrays, material characterization, and acoustic intensity vector field mapping

Visualizing Interior And Exterior Jet Aircraft Noise

In today\u27s competitive aerospace industry, the quest for quiet has drawn significant attention to both the interior and exterior design of an airplane. Understanding the noise generation mechanisms of a jet aircraft is a crucial first step toward developing the most cost-effective noise and vibrations abatement methods. In this investigation, the Helmholtz Equation Least Squares (HELS) based nearfield acoustic holography will be used to understand noise transmission caused by jet engine and turbulence into the fuselage of a jet aircraft cruising at 30,000 ft. Modern propulsive jet engines produce exterior noise sources with a high amplitude noise field and complicated characteristics, which makes them very difficult to characterize. In particular, there are turbulent eddies that are moving through the jet at high speeds along the jet boundary. These turbulent eddies in the shear layer produce a directional and frequency dependent noise. The original HELS approach assumes a spherical source at the origin and computes the acoustic field based on spherical emission from this source. This assumption of one source at the origin is not sufficient to characterize a complex source like a jet. As such, a modified HELS approach is introduced that will help improve the source characterization as it is not dependent on a single source at the origin but a number of virtual sources throughout the space. Custom microphones are created to take acoustic pressure measurements around the jet engine. These measured acoustic pressures are then taken as input to the modified HELS algorithm to visualize the noise pattern of a subsonic jet engine