System For Anomaly And Failure Detection (SAFD) System Development - Info and Reading Options
By OReilly, D
"System For Anomaly And Failure Detection (SAFD) System Development" and the language of the book is English.
“System For Anomaly And Failure Detection (SAFD) System Development” Metadata:
- Title: ➤ System For Anomaly And Failure Detection (SAFD) System Development
- Author: OReilly, D
- Language: English
“System For Anomaly And Failure Detection (SAFD) System Development” Subjects and Themes:
- Subjects: ➤ CRACK PROPAGATION - HIGH TEMPERATURE - STRESS-STRAIN DIAGRAMS - STRESS RATIO - STRAIN RATE - CERAMICS - STRESS-STRAIN RELATIONSHIPS - STRAIN DISTRIBUTION - STRAIN MEASUREMENT - FATIGUE (MATERIALS) - DYNAMIC TESTS - FATIGUE TESTS - WEIBULL DENSITY FUNCTIONS
Edition Identifiers:
- Internet Archive ID: nasa_techdoc_19970015018
AI-generated Review of “System For Anomaly And Failure Detection (SAFD) System Development”:
"System For Anomaly And Failure Detection (SAFD) System Development" Description:
The Internet Archive:
Task assignment 233 is a continuation of Task 23 which specified developing a platform for executing the System for Anomaly and Failure Detection (SAFD) algorithm during hot fire tests at Technology Test Bed (TTB) and installing the SAFD algorithm on that platform. Two units were built and installed in the Hardware Simulation Lab and at the TTB in December 1991. Since that time, efforts have been toward improving and maintaining the systems, improving the algorithm, performing additional tests to prove the feasibility of the algorithm, and supporting hot fire testing. This document addresses the work done since the last report of January 1995 which closed Task 23. The SAFD algorithm was developed to augment the current redline system used in the Space Shuttle Main Engine Controller (SSMEC). The primary goal was to save hardware during hot fire test failures. Execution against previous hot fire tests demonstrated that the SAFD algorithm can often detect engine failures prior to the redline system detecting them and, in some cases, this early detection could save significant hardware. The algorithm operates continuously at 40 ms intervals from start 7.00 seconds to shutdown as long as the engine is in mainstage normal. It currently monitors 21 parameters and includes provisions for sensor qualification. The algorithm uses simple equations to predict parameter values based on Pc Reference and inlet pressures. The limits are established around these predicted values. A five sample running average is maintained for each qualified parameter and is compared to the limits each cycle. The parameters are weighted for their contribution to cut and if the total weight of parameters out of limits exceeds the cut value, SAFD will request shutdown. The algorithm includes two methods of sensor qualification; rate and range. The rate limit qualification disqualifies a parameter if the parameter moves more than the rate qualification limit in a 40 ms period. The range limits include an upper and lower limit for the parameter. The rate and range limits are set individually for each parameter. All values for limits, delays, rates, weights, etc. are changeable by adaptation data. The work on SAFD under Task 233 included improving the platform and the algorithm, deriving 'standard' adaptation data, testing the algorithm against hot fire test data, providing support for operations at the TTB, providing routine maintenance, and moving the unit at TTB to SSC.
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