4
Integrating Lead Innovative Technologies Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics DSI developed a detailed model of the fuel control assembly for an airplane Detailed Diagnostics tests for fault isolation were developed Prognostics were added for the fuel transfer pump Prognostics uses P, fuel flow rate and Cmd inputs to assess pump degradation

Integrating Lead Innovative Technologies Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics DSI developed

Embed Size (px)

Citation preview

Page 1: Integrating Lead Innovative Technologies  Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics  DSI developed

Integrating Lead Innovative Technologies

Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics

DSI developed a detailed model of the fuel control assembly for an airplane

Detailed Diagnostics tests for fault isolation were developed

Prognostics were added for the fuel transfer pump

Prognostics uses P, fuel flow rate and Cmd inputs to assess pump degradation

Page 2: Integrating Lead Innovative Technologies  Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics  DSI developed

Fuel Control Assembly Model

Page 3: Integrating Lead Innovative Technologies  Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics  DSI developed

Hea

d

Flow Rate

Best Eff. Point (BEP)

NPSHR

NPSHA

Ideal

Degradation Effects

Pump Prognostics Explained

Assaad Krichene
Fuzzy Membership functions account for statistical variability. Green for nominal operation, yellow and red for different levels of degradation
Assaad Krichene
NPSHA: Net Positive Suction Head AvailableNPSHR: Net Positive Suction Head Required
Page 4: Integrating Lead Innovative Technologies  Impact Technologies’ Physics-Based Prognostics with DSI International’s Systems Diagnostics  DSI developed

Prognostics “Added Value”

Isolation in just one “test” Set of anticipated diagnostics tests to fail Can provide an anticipated time to failure

with confidence bounds based on future operating profile

May be used to change diagnostics tests order to isolate faults more efficiently i.e. with fewer tests

May provide updates to reliability curves (updated MTBF) for simulations