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

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

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 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

Vehicle Integrated Propulsion Research for the Study of Health Management Capabilities

Presentation on vehicle integrated propulsion research results and planning. This research emphasizes the testing of advanced health management sensors and diagnostics in an aircraft engine that is operated through multiple baseline and fault conditions

Evaluating visible derivative spectroscopy by varimax-rotated, principal component analysis of aerial hyperspectral images from the western basin of Lake Erie

The Kent State University (KSU) spectral decomposition method provides information about the spectral signals present in multispectral and hyperspectral images. Pre-processing steps that enhance signal to noise ratio (SNR) by 7.37–19.04 times, enables extraction of the environmental signals captured by the National Aeronautics and Space Administration (NASA) Glenn Research Center\u27s, second generation, Hyperspectral imager (HSI2) into multiple, independent components. We have accomplished this by pre-processing of Level 1 HSI2 data to remove stripes from the scene, followed by a combination of spectral and spatial smoothing to further increase the SNR and remove non-Lambertian features, such as waves. On average, the residual stochastic noise removed from the HSI2 images by this method is 5.43 ± 1.42%. The method also enables removal of a spectrally coherent residual atmospheric bias of 4.28 ± 0.48%, ascribed to incomplete atmospheric correction. The total noise isolated from signal by the method is thu

A COTS RF Optical Software Defined Radio for the Integrated Radio and Optical Communications Test Bed

The Integrated Radio and Optical Communications (iROC) project at the National Aeronautics and Space Administration (NASA) is investigating the merits of a hybrid radio frequency (RF) and optical communication system for deep space missions. In an effort to demonstrate the feasibility and advantages of a hybrid RFOptical software defined radio (SDR), a laboratory prototype was assembled from primarily commercial-off-the-shelf (COTS) hardware components. This COTS platform has been used to demonstrate simultaneous transmission of the radio and optical communications waveforms through to the physical layer (telescope and antenna). This paper details the hardware and software used in the platform and various measures of its performance. A laboratory optical receiver platform has also been assembled in order to demonstrate hybrid free space links in combination with the transmitter

A Methodological Framework for the Evaluation of Syndromic Surveillance Systems: A Case Study of England

Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different types outbreaks with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response

GRC Remote Sensing Campaign of Harmful Algal Blooms 2017-2019

This presentation goes over the harmful algal bloom monitoring with different in house hyperspectral imagers