Topics
TestActivity
A prototype Optical Plume Anomaly Detection (OPAD) system is now installed on the space shuttle main engine (SSME) Technology Test Bed (TTB) at MSFC. The OPAD system requirements dictate the need for fast, efficient data processing techniques. To address this need of the OPAD system, a study was conducted into how artificial neural networks could be used to assist in the analysis of plume spectral data
The Photonic Processing group is engaged in applied research on optical processors in support of the...
Neural networks trained using mass spectra data from the National Institute of Standards and Technol...
To determine the readiness of a rocket engine, and facilitate decisions on continued use of the engi...
The space shuttle main engine (SSME) became the subject of plume emission spectroscopy in 1986 when ...
The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts s...
Space Shuttle Main Engine fault detection systems typically rely on sensor data analysis via redunda...
The Optical Plume Anomaly Detection (OPAD) pro-gram at the NASA Marshall Space Flight Center is UB-i...
The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods...
An on-board autonomous exploration system that fuses data from multiple sensors, and makes decisions...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
The constant emission of polluting gases is causing an urgent need for timely detection of harmful g...
The constant emission of polluting gases is causing an urgent need for timely detection of harmful g...
Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine...
The Photonic Processing group is engaged in applied research on optical processors in support of the...
Neural networks trained using mass spectra data from the National Institute of Standards and Technol...
To determine the readiness of a rocket engine, and facilitate decisions on continued use of the engi...
The space shuttle main engine (SSME) became the subject of plume emission spectroscopy in 1986 when ...
The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts s...
Space Shuttle Main Engine fault detection systems typically rely on sensor data analysis via redunda...
The Optical Plume Anomaly Detection (OPAD) pro-gram at the NASA Marshall Space Flight Center is UB-i...
The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods...
An on-board autonomous exploration system that fuses data from multiple sensors, and makes decisions...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
In this paper, artificial neural networks (ANN), which are known for their ability to model nonlinea...
The constant emission of polluting gases is causing an urgent need for timely detection of harmful g...
The constant emission of polluting gases is causing an urgent need for timely detection of harmful g...
Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine...
The Photonic Processing group is engaged in applied research on optical processors in support of the...
Neural networks trained using mass spectra data from the National Institute of Standards and Technol...
To determine the readiness of a rocket engine, and facilitate decisions on continued use of the engi...
Add to ORKG