Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters
Abstract
1. Introduction
2. System Configuration and Physical Model
2.1. System Configuration
2.2. Physical Model
2.2.1. Spring Cracking
2.2.2. Seals Wear
3. Scenario Definition and Simulation
3.1. On-Ground Tests
3.2. In-Flight Conditions
4. Feature Selection
5. PHM Algorithm
5.1. Fault Detection
5.2. Failure Prognosis
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Abbreviations
CRA | Cumulative relative accuracy |
FFT | Fast Fourier Transform |
LVDT | Linear Variable Differential Transformer |
PHM | Prognostics and health management |
Probability density function | |
RA | Relative accuracy |
RMS | Root Mean Square |
RUL | Remaining useful life |
SCAS | Stability and command augmentation system |
Symbols
a | Depth of crack, m |
A | Area, m2 |
C | Spring index R/r, dimensionless |
D | Diameter of the spring coil, m |
F | Axial force action on the spring, N |
FT(η) | Geometrical factor, dimensionless |
G | Shear modulus, Pa |
i | Current, A |
J | Polar second moment of area, m4 |
K | Spring stiffness, N/m |
Ki1 | First leakage parameter, m3/s/Pa |
Ki2 | Second leakage parameter, m3/s/ |
KIII | Stress intensity factor, Pa |
La | Friction work, J |
N | Number of spring turns, dimensionless |
Ql | Volumetric flow rate, m3/s |
R | Radius of the spring coil, m |
r | Radius of the spring wire, m |
x | Displacement, m |
β | Experimental material parameter, N/m |
γ | Shear strain, dimensionless |
Δp | Differential pressure, Pa |
δ | Spring displacement, m |
ε | Opening angle of the crack, rad |
η | Dimensionless crack depth a/(2r) |
λ | Thickness of removed material, m |
τ | Shear stress, Pa |
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Occurrence | Command | Amplitude (mm) | Frequency (Hz) |
---|---|---|---|
2% | XSCAS | 0 | 0 |
Xi | 50 | 0.05 | |
60% | XSCAS | 0.3 | 2 |
Xi | 0.5 | 1.5 | |
30% | XSCAS | 0.3 | 1.5 |
Xi | 0.8 | 1 | |
8% | XSCAS | 2 | 0.8 |
Xi | 10 | 0.8 |
Feature | Description | |
---|---|---|
G1 | mean(i) | Current mean value |
G2 | (max(x)-set)/set | % displacement overshoot |
G3 | i/x | Current/displacement |
I1 | abs(fft(x))(2Hz) | Displacement FFT amplitude at 2 Hz |
I2 | mean(xcorr(i,ih)) | Mean value cross-correlation with respect to baseline (current) |
I3 | mean(xcorr(x,xh)) | Mean value cross-correlation with respect to baseline (displacement) |
I4 | mean(xcorr(x)) | Displacement auto-correlation |
I5 | rms(abs(fft(x))) | RMS displacement FFT amplitude |
I6 | rms(x) | Displacement RMS |
I7 | rms(i)/rms(x) | RMS current/RMS displacement |
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Share and Cite
Nesci, A.; De Martin, A.; Jacazio, G.; Sorli, M. Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters. Aerospace 2020, 7, 20. https://doi.org/10.3390/aerospace7030020
Nesci A, De Martin A, Jacazio G, Sorli M. Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters. Aerospace. 2020; 7(3):20. https://doi.org/10.3390/aerospace7030020
Chicago/Turabian StyleNesci, Andrea, Andrea De Martin, Giovanni Jacazio, and Massimo Sorli. 2020. "Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters" Aerospace 7, no. 3: 20. https://doi.org/10.3390/aerospace7030020
APA StyleNesci, A., De Martin, A., Jacazio, G., & Sorli, M. (2020). Detection and Prognosis of Propagating Faults in Flight Control Actuators for Helicopters. Aerospace, 7(3), 20. https://doi.org/10.3390/aerospace7030020