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Dynamic Pressure Sensing for the Flight Test Data System

This thesis describes the design, assembly, and test of the FTDS-K, a new device in the Boundary Layer Data System (BLDS) family of flight data acquisition systems. The FTDS-K provides high-frequency, high-gain data acquisition capability for up to two pressure sensors and an additional three low-frequency pressure sensors. Development of the FTDS-K was separated into a core module, specialized analog subsystem, and practical testing of the FTDS-K in a flow measurement mission. The core module combines an nRF52840-based microcontroller module, switching regulator, microSD card, real-time clock, temperature sensor, and trio of pressure sensors to provide the same capabilities as previous-generation BLDS-P devices. An expansion header is included in the core module to allow additional functionality to be added via daughter boards. An analog signal chain comprised of two-stage amplification and fourth-order active antialiasing filters was implemented as a daughter board to provide an AC-coupled end-to-end gain of 7,500 and a DC-coupled end-to-end gain of 50. This arrangement was tested in a wind tunnel to demonstrate that sensors with a full-scale range of 103 kPa can be used to reliably discriminate between laminar and turbulent flows based on pressure fluctuation differences on the order of tens of Pa. A combination of wind-off correction and band-filtering was used to reduce the effect of inherent and induced electrical noise, while two-sensor correlation was tested and shown to be effective at removing certain types of noise. Total power consumption for the FTDS-K in a representative mission is 208 mW, which translates to an operational endurance of 9 hours with 2 AAA LiFeS2 cells at -40°C.

Identiferoai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3580
Date01 December 2019
CreatorsGoupil, Marc Y
PublisherDigitalCommons@CalPoly
Source SetsCalifornia Polytechnic State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMaster's Theses

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