Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis
Abstract
:1. Introduction
2. Algorithm Principle
3. Polynomial Fitting Model Based on Least Squares Method
4. Calculation Model and Order Selection
5. Case Study
Y1 = 1.1 × Z3 +15 × Z2 + 57 × Z + 9.3 × 102
Y1 = -5.8 × Z4 − 15 × Z3 + 17 × Z2 + 95 × Z + 9.1 × 102
Y1 = −15 × Z5−61 × Z4 − 40 × Z3 + 77 × Z2 +95Z + 9.1 × 102
Y1 = −5.3 × Z6 − 37 × Z5 − 75 × Z4 − 15 × Z3 + 94 × Z2 + 87 × Z +9.1 × 102
Y2 = 0.53 × Z3 + 6.3 × Z2 + 20 × Z + 9.5 × 102
Y2 = −2.5 × Z4 − 6.2 × Z3 + 7.1 × Z2 + 26 × Z + 9.5 × 102
Y2 = −5.3 × Z5 − 22 × Z4 − 15 × Z3 + 29 × Z2 + 34 × Z + 9.5 × 102
Y2 = −1.2 × Z6 − 10 × Z5 − 25 × Z4 − 9.8 × Z3 + 32 × Z2 + 32 × Z + 9.5 × 102
Y3 = 0.074 × Z3 + 2.8 × Z2 + 11 × Z + 9.7 × 102
Y3 = −0.9 × Z4 − 2.4 × Z3 + 3.1 × Z2 + 13 × Z + 9.7 × 102
Y3 = −2.7 × Z5 − 11 × Z4 − 7 × Z3 + 14 × Z2 + 18 × Z + 9.7 × 102
Y3 = −1.7 × Z6 − 9.7 × Z5 − 15 × Z4 + 1.1 × Z3 + 19 × Z2 + 15 × Z + 9.7 × 102
Y4 = 0.074 × Z3 + 2.8 × Z2 + 11 × Z + 9.7 × 102
Y4 = −0.9 × Z4 − 2.4 × Z3 + 3.1 × Z2 + 13 × Z + 9.7 × 102
Y4 = −2.7 × Z5 − 11 × Z4 − 7 × Z3 + 14 × Z2 + 18 × Z + 9.7 × 102
Y4 = −1.7 × Z6 − 9.7 × Z5 − 15 × Z4 +1.1 × Z3 +19 × Z2 + 15 × Z + 9.7 × 102
6. Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Saserial Number | Parameter Abbreviation | Parameter Explanation |
---|---|---|
1 | E1 FFlow | fuel flow |
2 | E1 OilT | lubricating oil temperature |
3 | E1 Oilp | Oil pressure |
4 | E1 RPM | Engine speed |
5 | E1 CHT1 | No. 1 cylinder temperature |
6 | E1 CHT2 | No. 2 cylinder temperature |
7 | E1 CHT3 | No. 3 cylinder temperature |
8 | E1 CHT4 | No. 4 cylinder temperature |
9 | E1 EGT1 | No. 1 cylinder exhaust gas temperature |
10 | E1 EGT2 | No. 2 cylinder exhaust gas temperature |
11 | E1 EGT3 | No. 3 cylinder exhaust gas temperature |
12 | E1 EGT4 | No.4 cylinder exhaust gas temperature |
Flight Data | RPM | EGT1 | EGT2 | EGT3 | EGT4 |
---|---|---|---|---|---|
1 | 1026.8 | 864.39 | 936.05 | 957.78 | 954.93 |
2 | 1039.2 | 868.36 | 936.71 | 957.77 | 955.47 |
3 | 1058.8 | 878.23 | 937.76 | 958.14 | 956.81 |
4 | 1049.2 | 885.51 | 941.7 | 960.2 | 959.41 |
5 | 1056.2 | 898.87 | 944.24 | 964.63 | 962.23 |
6 | 1069 | 906.1 | 945.41 | 967.03 | 964.14 |
7 | 1080 | 912.3 | 948.98 | 967.44 | 966.89 |
8 | 1082.3 | 923.17 | 952.29 | 967.77 | 970.15 |
9 | 1081 | 935.1 | 955.88 | 967.77 | 971.42 |
10 | 1081.8 | 945.63 | 960.01 | 969.55 | 973.29 |
11 | 1093.1 | 954.94 | 963.35 | 971.52 | 975.99 |
12 | 1090.2 | 963.98 | 965.81 | 975.16 | 978.94 |
13 | 1083.2 | 971.95 | 969.14 | 978.3 | 981.44 |
14 | 1087.7 | 978.44 | 972.41 | 979.23 | 981.44 |
15 | 1093 | 978.44 | 973.81 | 980.28 | 987.47 |
16 | 1088.6 | 990.26 | 975.82 | 981.49 | 990.65 |
17 | 1088.8 | 995.62 | 977.37 | 981.88 | 991.54 |
18 | 1093.7 | 999.37 | 980.16 | 983.5 | 993.24 |
19 | 1093.2 | 1002.45 | 981.44 | 986.47 | 995.57 |
20 | 1084.6 | 1003.41 | 984.02 | 988.37 | 997.35 |
Order | Real Value | Predicted Value | Error (%) |
---|---|---|---|
two | 906.1 | 871.33 | 3.8 |
three | 906.1 | 873.59 | 3.6 |
four | 906.1 | 878.45 | 3.0 |
five | 906.1 | 610.41 | 3.6 |
six | 906.1 | 871.85 | 3.8 |
Order | Real Value | Predicted Value | Error (%) |
---|---|---|---|
two | 937.76 | 940.87 | 0.3 |
three | 937.76 | 930.90 | 0.7 |
four | 937.76 | 935.75 | 0.2 |
five | 937.76 | 934.58 | 0.3 |
six | 937.76 | 812.39 | 13.3 |
Order | Real Value | Predicted Value | Error (%) |
---|---|---|---|
two | 958.14 | 958.3734 | 2.2 |
three | 958.14 | 958.5752 | 2.2 |
four | 958.14 | 961.1482 | 2.4 |
five | 958.14 | 955.5948 | 2.0 |
six | 958.14 | 969.9161 | 3.4 |
Order | Real Value | Predicted Value | Error (%) |
---|---|---|---|
two | 956.81 | 953.6518 | 0.3 |
three | 956.81 | 953.612 | 0.3 |
four | 956.81 | 959.1251 | 0.2 |
five | 956.81 | 954.4378 | 0.3 |
six | 956.81 | 937.3811 | 2.0 |
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Chen, N.; Sun, Y.; Wang, Z.; Peng, C. Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis. Appl. Sci. 2022, 12, 2545. https://doi.org/10.3390/app12052545
Chen N, Sun Y, Wang Z, Peng C. Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis. Applied Sciences. 2022; 12(5):2545. https://doi.org/10.3390/app12052545
Chicago/Turabian StyleChen, Nongtian, Youchao Sun, Zongpeng Wang, and Chong Peng. 2022. "Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis" Applied Sciences 12, no. 5: 2545. https://doi.org/10.3390/app12052545
APA StyleChen, N., Sun, Y., Wang, Z., & Peng, C. (2022). Correction and Fitting Civil Aviation Flight Data EGT Based on RPM: Polynomial Least Squares Analysis. Applied Sciences, 12(5), 2545. https://doi.org/10.3390/app12052545