Designing Shading Schemes for Microphone Phased Arrays
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Intracochlear electric potential of anesthetized cats recorded with potassium filled glass micropipets, determining magnitude and phase of responses
A theoretical analysis is presented for the evaluation of correlation functions of many spatially separated noise sources in a jet. A one-dimensional model is considered in which the noise sources are located on the axis of the jet downstream of the nozzle. The theory for extracting the spatial distribution from far field cross-correlations by signal analysis is derived. The advantage of this method is that difficult numerical inversions are not needed.
Reaction wheel vibration was found to induce out of specification sidebands on the carrier frequencies of some spacecraft components containing mechanical voltage control oscillators (VCOs). Concurrent investigations were performed to redesign the VCOs to reduce their response to the wheel vibration, and to design a reaction wheel isolation system to reduce the vibration input to the affected components. Component level tests indicated that both efforts provided viable solutions. The redesigned VCO will be incorporated into future spacecraft in the series, while affected spacecraft already in production will be retrofitted with the reaction wheel isolation system.
Tables are provided of measured sonic boom signature data derived from supersonic flyover tests of the XB-70, B-58 and F-104 aircraft for ranges of altitude and Mach number. These tables represent a convenient hard copy version of available electronic files and complement preliminary information included in a reference National Sonic Boom Evaluation Office document.
Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.
Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.
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Acoustic phased array flyover noise measurements were acquired as part of the Boeing 737 MAX-7 NASA Advanced Inlet Liner segment of the Quiet Technology Demonstrator 3 (QTD3) flight test program. This paper reports on the processes used for separating and quantifying the engine inlet, exhaust and airframe noise source components and provides sample phased array-based comparisons of the component noise source levels associated with the inlet liner treatment configurations. Full scale flyover noise testing of NASA advanced inlet liners was conducted as part of the Quiet Technology Demonstrator 3 flight test program in July and August of 2018. Details on the inlet designs and testing are provided in the companion paper of Reference 1. The present paper provides supplemental details relating to the acoustic phased array portion of the analyses provided in Ref. 1. In brief, the test article was a Boeing 737MAX-7 aircraft with a modified right hand (starboard side) engine inlet, which consisted of either a production inlet liner, a NASA designed inlet liner or a simulated hard wall configuration (accomplished by applying speed tape over the inlet acoustic treatment areas). In all three configurations, the engine forward fan case acoustic panel was replaced with a unperforated (hardwall) panel. No other modifications to any other acoustic treatment areas were made. The left hand (port side) engine was a production engine and was flown at idle thrust for all measurements in order to isolate the effects of the inlet liners to the right hand engine. As described in Ref. 1, the NASA inlet treatment consists of laterally cut slots (cut perpendicular to the flow direction) which are designed to reduce excrescence drag while maintaining or exceeding the liner acoustic noise reduction capabilities. The NASA inlet liner consists of a Multi-Degree of Freedom (MDOF) design with two breathable septum layers inserted into each honeycomb cell [1]. The aircraft noise measurements were acquired for both takeoff (flaps 1 setting, gear up) and approach (flaps 30 gear up and gear down) configurations. The inlet and flight test configurations are summarized in Table 1. Table 1: Inlet Treatment and Flight Configurations Inlet Forward Fan Case Aircraft Production Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down NASA Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down Hardwall Hardwall Flaps 1, gear up; flaps 30 gear up; flaps 30 gear down III.Test Description and Hardware The flight testing was conducted at the Grant County airport in Moses Lake, WA, between 27 July and 6 August 2018. The noise measurement instrumentation included 8 flush dish microphones arranged in a noise certification configuration as well as an 840 microphone phased array. The flush dish microphones were used to quantify the levels and differences in levels between the various inlet treatments. The phased array was used to separate and quantify the narrowband (tonal) and broadband noise component levels from the engine inlet/exhaust and from the airframe. Phased array extraction of the broadband component was critical to this study because it allowed for the separation of the inlet component from the total airplane level noise even when it was significantly below the total level. Figure 1 provides an overview of the phased array microphone layout as well as a detailed image of an individual phased array microphone mounted in a plate holder (the microphone sensor is the dot in the center of the plate). The ground plane ensemble array microphones (referred to as “ensemble array” in this paper) were mounted in plates with “flower petal” edges designed to minimize edge scattering effects. Fig. 1 Flyover test microphone layout. The phased array configuration was the result of a progressive development of concepts originally implemented in Ref. 2 and refined over the following years, consisting namely of multiple multi-arm logarithmic spiral subarrays designed to cover overlapping frequency ranges and optimized for various aircraft emission angles. For the present case, the signals from all 840 microphones were acquired on a single system. The 840 microphones were parsed into 11 primary subarray sets spanning from smallest to largest aperture size and labeled accordingly as “a, b, …, k”, where “a” corresponds to the smallest fielded subarray and “k” corresponds to the largest aperture subarray. The apertures ranged from approximately 10 ft to 427 ft in size (in the flight direction) with the subarrays consisting of between 215 and 312 microphones. Figure 2 shows three such subarrays, k, h and a. As done in Ref. 2, microphones were shared between subarrays in order to reduce total channel count. Fig. 2 Sample subarray sizes (20° from overhead – refer to Figure 3a discussion). In addition to the above, each of the 11 primary subarray sets consisted of four subarrays optimized to provide near equivalent array spatial resolution in both the flight and lateral directions within 30 degrees of overhead (i.e., airplane directly above the center of the array), namely, at angles of 0, ±10, ±20 and ±30 degrees relative to overhead where angle is defined as shown in Figure 3a. This allowed for optimized aircraft noise measurements from 60 to 120 degree emission angle.6 An example of this pletharray design is shown in Figure 3b for the k subarray. When the aircraft is at overhead, the microphones indicated by the blue markers are used for beamforming. When the aircraft is at angles ±10 degrees from overhead, both the blue and red colored microphones are used, and so on for the ±20 and ±30 degree aircraft locations. See Ref. 3 for extensive details on pletharray design for aeroacoustic phased array testing. 6 In the discussions that follow, emission angle values are used. These are the angles at the time sound is emitted relative to the engine axis and are calculated based on flight path angle, body aircraft body angle with respect to the relative wind direction, and engine axis angle relative to aircraft body angle.
The acoustic capability of the NASA Lewis 9 by 15 Foot Low Speed Wind Tunnel has been significantly improved by reducing the background noise levels measured by in-flow microphones. This was accomplished by incorporating streamlined microphone holders having a profile developed by researchers at the NASA Ames Research Center. These new holders were fabricated for fixed mounting on the tunnel wall and for an axially traversing microphone probe which was mounted to the tunnel floor. Measured in-flow noise levels in the tunnel test section were reduced by about 10 dB with the new microphone holders compared with those measured with the older, less refined microphone holders. Wake interference patterns between fixed wall microphones were measured and resulted in preferred placement patterns for these microphones to minimize these effects. Acoustic data from a model turbofan operating in the tunnel test section showed that results for the fixed and translating microphones were equivalent for common azimuthal angles, suggesting that the translating microphone probe, with its significantly greater angular resolution, is preferred for sideline noise measurements. Fixed microphones can provide a local check on the traversing microphone data quality, and record acoustic performance at other azimuthal angles.
Results are described of an analytical study of the accuracy and limitations of a technique that permits the mathematical extrapolation of near-field noise data to far-field conditions. The effects of the following variables on predictive accuracy of the far-field pressure were examined: (1) number of near-field microphones; (2) length of source distribution; (3) complexity of near-field and far-field distributions; (4) source-to-microphone distance; and (5) uncertainties in microphone data and imprecision in the location of the near-field microphones. It is shown that the most important parameters describing predictive accuracy are the number of microphones, the ratio of source length to acoustic wavelength, (L/wavelength), and the error in location of near-field microphones. If microphone measurement and location errors are not included, then far-field pressures can be accurately predicted up to L/wavelength values of 15 using approximately 50 microphones. For maximum microphone location errors of + or - 1 cm, only an accuracy of + or - 2-1/2 db can be attained with approximately 40 microphones for the highest L/wavelength of 10.
Results are presented for an analytical study of the accuracy and limitations of a technique that permits the mathematical extrapolation of near-field noise data to far-field conditions. The effects of the following variables on predictive accuracy of the far-field pressure were examined: (1) number of near-field microphones; (2) length of source distribution; (3) complexity of near-field and far-field distributions; (4) source-to-microphone distance; and (5) uncertainties in microphone data and imprecision in the location of the near-field microphones. It is shown that the most important parameters describing predictive accuracy are the number of microphones, the ratio of source length to acoustic wavelength (L/lambda), and the error in location of near-field microphones. For maximum microphone location errors of plus or minus 1 cm, only an accuracy of plus or minus 2.5 dB can be attained with approximately 40 microphones for the highest L/lambda of 10.