One-Dimensional Scanning Approach to Shock Sensing

Measurement tools for high speed air flow are sought both in industry and academia. Particular interest is shown in air flows that exhibit aerodynamic shocks. Shocks are accompanied by sudden changes in density, pressure, and temperature. Optical detection and characterization of such shocks can be difficult because the medium is normally transparent air. A variety of techniques to analyze these flows are available, but they often require large windows and optical components as in the case of Schlieren measurements and/or large operating powers which precludes their use for in-flight monitoring and applications. The one-dimensional scanning approach in this work is a compact low power technique that can be used to non-intrusively detect shocks. The shock is detected by analyzing the optical pattern generated by a small diameter laser beam as it passes through the shock. The optical properties of a shock result in diffraction and spreading of the beam as well as interference fringes. To investigate the feasibility of this technique a shock is simulated by a 426 m diameter optical fiber. Analysis of results revealed a direct correlation between the optical fiber or shock location and the beam s diffraction pattern. A plot of the width of the diffraction pattern vs. optical fiber location reveals that the width of the diffraction pattern was maximized when the laser beam is directed at the center of the optical fiber. This work indicates that the one-dimensional scanning approach may be able to determine the location of an actual shock. Near and far field effects associated with a small diameter laser beam striking an optical fiber used as a simulated shock are investigated allowing a proper one-dimensional scanning beam technique

Self Diagnostic Accelerometer Field Programmable Gate Array (SDA FPGA)

A self-diagnostic accelerometer (SDA) field programmable gate array (FPGA) may be capable of real time or near-real time diagnostic processing to determine potential accelerometer issues during flight or other mission critical operational situations. The SDA FPGA may determine accelerometer structural health and an attachment condition using an electronics system that is smaller, more energy efficient, and more cost effective than previous diagnostic tools. Advantages of the system may include diagnosing sensors automatically, immediately, actively (i.e., confirming the fault), and consistently, without the influence of a human operator. Customizable SDA algorithms may be adjusted to the specific needs of the sensor/environment

Feasibility Study of Jupiter Icy Moons Orbiter Permanent Magnet Alternator Start Sequence

The Jupiter Icy Moons Orbiter (JIMO) mission was a proposed, (recently cancelled) long duration science mission to study three moons of Jupiter: Callisto, Ganymede, and Europa. One design of the JIMO spacecraft used a nuclear heat source in conjunction with a Brayton rotating machine to generate electrical power for the electric thrusters and the spacecraft bus. The basic operation of the closed cycle Brayton system was as follows. The working fluid, a heliumxenon gas mixture, first entered a compressor, then went through a recuperator and hot-side heat exchanger, then expanded across a turbine that drove an alternator, then entered the cold-side of the recuperator and heat exchanger and finally returned to the compressor. The spacecraft was to be launched with the Brayton system off-line and the nuclear reactor shut down. Once the system was started, the helium-xenon gas would be circulated into the heat exchangers as the nuclear reactors were activated. Initially, the alternator unit would operate as a motor so as to drive the turbine and compressor to get the cycle started. This report investigated the feasibility of the start up sequence of a permanent magnet (PM) machine, similar in operation to the alternator unit, without any position or speed feedback sensors ("sensorless") and with a variable load torque. It is found that the permanent magnet machine can start with sensorless control and a load torque of up to 30 percent of the rated value

Airborne Monitoring of Harmful Algal Blooms over Lake Erie

The Hyperspectral Imager mounted to an aircraft was used to develop a remote sensing capability to detect the pigment Phycocyanin, an indicator of Microcystis, in low concentration as an early indicator of harmful algal bloom prediction

Improved Signal Processing Technique Leads to More Robust Self Diagnostic Accelerometer System

The self diagnostic accelerometer (SDA) is a sensor system designed to actively monitor the health of an accelerometer. In this case an accelerometer is considered healthy if it can be determined that it is operating correctly and its measurements may be relied upon. The SDA system accomplishes this by actively monitoring the accelerometer for a variety of failure conditions including accelerometer structural damage, an electrical open circuit, and most importantly accelerometer detachment. In recent testing of the SDA system in emulated engine operating conditions it has been found that a more robust signal processing technique was necessary. An improved accelerometer diagnostic technique and test results of the SDA system utilizing this technique are presented here. Furthermore, the real time, autonomous capability of the SDA system to concurrently compensate for effects from real operating conditions such as temperature changes and mechanical noise, while monitoring the condition of the accelerometer health and attachment, will be demonstrated

Self Diagnostic Accelerometer Testing on the C-17 Aircraft

The self diagnostic accelerometer (SDA) developed by the NASA Glenn Research Center was tested for the first time in an aircraft engine environment as part of the Vehicle Integrated Propulsion Research (VIPR) program. The VIPR program includes testing multiple critical flight sensor technologies. One such sensor, the accelerometer, measures vibrations to detect faults in the engine. In order to rely upon the accelerometer, the health of the accelerometer must be ensured. The SDA is a sensor system designed to actively determine the accelerometer structural health and attachment condition, in addition to vibration measurements. The SDA uses a signal conditioning unit that sends an electrical chirp to the accelerometer and recognizes changes in the response due to changes in the accelerometer health and attachment condition. To demonstrate the SDAs flight worthiness and robustness, multiple SDAs were mounted and tested on a C-17 aircraft engine. The engine test conditions varied from engine off, to idle, to maximum power. The SDA attachment conditions were varied from fully tight to loose. The newly developed SDA health algorithm described herein uses cross correlation pattern recognition to discriminate a healthy from a faulty SDA. The VIPR test results demonstrate for the first

Wind Tunnel Testing of a One-Dimensional Laser Beam Scanning and Laser Sheet Approach to Shock Sensing

A 15- by 15-cm supersonic wind tunnel application of a one-dimensional laser beam scanning approach to shock sensing is presented. The measurement system design allowed easy switching between a focused beam and a laser sheet mode for comparison purposes. The scanning results were compared to images from the tunnel Schlieren imaging system. The tests revealed detectable changes in the laser beam in the presence of shocks. The results lend support to the use of the one-dimensional scanning beam approach for detecting and locating shocks in a flow, but some issues must be addressed in regards to noise and other limitations of the system

Self Diagnostic Accelerometer for Mission Critical Health Monitoring of Aircraft and Spacecraft Engines

A self diagnostic accelerometer system has been shown to be sensitive to multiple failure modes of charge mode accelerometers. These failures include sensor structural damage, an electrical open circuit and most importantly sensor detachment. In this paper, experimental work that was performed to determine the capabilities of a self diagnostic accelerometer system while operating in the presence of various levels of mechanical noise, emulating real world conditions, is presented. The results show that the system can successfully conduct a self diagnostic routine under these conditions

Real time HABs mapping using NASA Glenn hyperspectral imager

The hyperspectral imaging system (HSI) developed by the NASA Glenn Research Center was used from 2015 to 2017 to collect high spatial resolution data over Lake Erie and the Ohio River. Paired with a vicarious correction approach implemented by the Michigan Tech Research Institute, radiance data collected by the HSI system can be converted to high quality reflectance data which can be used to generate near-real time (within 24 h) products for the monitoring of harmful algal blooms using existing algorithms. The vicarious correction method relies on imaging a spectrally constant target to normalize HSI data for atmospheric and instrument calibration signals. A large asphalt parking lot near the Western Basin of Lake Erie was spectrally characterized and was determined to be a suitable correction target. Due to the HSI deployment aboard an aircraft, it is able to provide unique insights into water quality conditions not offered by space-based solutions. Aircraft can operate under cloud cover and flight paths can be chosen and changed on-demand, allowing for far more flexibility than space-based platforms. The HSI is also able to collect data at a high spatial resolution (~1 m), allowing for the monitoring of small water bodies, the ability to detect small patches of surface scum, and the capability to monitor the proximity of blooms to targets of interest such as water intakes. With this new rapid turnaround time, airborne data can serve as a complementary monitoring tool to existing satellite platforms, targeting critical areas and responding to bloom events on-demand

Determining remote sensing spatial resolution requirements for the monitoring of harmful algal blooms in the Great Lakes

Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms\u27 spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 and HSI-3. Hyperspectral imagery is necessary in order to conduct experiments on differentiation of algal bloom types based on their spectral reflectance. In this analysis, imagery from September 19, 2016 was utilized to study the subpixel variability within the footprint of arbitrary sized pixels using several analysis techniques. This particular data set is utilized because it represents a worst case scenario where there is significant potential for public health concern due to high concentrations of microcystin toxin found in the water on this day and the concurrent observational challenges to accurately measure the algal bloom concentration variability with a remote sensing system due to the blooms high spatial variability. It has been determined that the optimal spatial resolution to monitor algal blooms in the Great Lakes is at most 50 m, and for much lower error 25 m, thus allowing for greater ease in identifying high concentration blooms near the surface. This resolution provides the best sensitivity to high concentration areas that are of significant importance in regard to human health and ecological damage