scholarly journals Fuzzy-Logic Analysis of the FDR Data of a Transport Aircraft in Atmospheric Turbulence

10.5772/37559 ◽  
2012 ◽  
Author(s):  
C. Edward ◽  
Ray C.
Keyword(s):  
Fuzzy Logic ◽  
Atmospheric Turbulence ◽  
Transport Aircraft ◽  
Fuzzy Logic Analysis

scholarly journals Structural Health Monitoring of Transport Aircraft with Fuzzy Logic Modeling

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Ray C. Chang ◽  
C. Edward Lan
Keyword(s):  
Fuzzy Logic ◽  
Structural Health Monitoring ◽  
Atmospheric Turbulence ◽  
Health Monitoring ◽  
Structural Flexibility ◽  
Monitoring Method ◽  
Logic Modeling ◽  
Transport Aircraft ◽  
Structural Health ◽  
Static Aeroelasticity

A structural health monitoring method based on the concept of static aeroelasticity is presented in this paper. This paper focuses on the estimation of these aeroelastic effects on older transport aircraft, in particular the structural components that are most affected, in severe atmospheric turbulence. Because the structural flexibility properties are mostly unknown to aircraft operators, only the trend, not the magnitude, of these effects is estimated. For this purpose, one useful concept in static aeroelastic effects for conventional aircraft structures is that under aeroelastic deformation the aerodynamic center should move aft. This concept is applied in the present paper by using the fuzzy-logic aerodynamic models. A twin-jet transport aircraft in severe atmospheric turbulence involving plunging motion is examined. It is found that the pitching moment derivatives in cruise with moderate to severe turbulence in transonic flight indicate some degree of abnormality in the stabilizer (i.e., the horizontal tail). Therefore, the horizontal tail is the most severely affected structural component of the aircraft probably caused by vibration under the dynamic loads induced by turbulence.

scholarly journals Fuzzy Logic-Based Aerodynamic Modeling with Continuous Differentiability

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Ray C. Chang
Keyword(s):  
Fuzzy Logic ◽  
Atmospheric Turbulence ◽  
Model Development ◽  
Unsteady Aerodynamics ◽  
Least Square Method ◽  
Least Square ◽  
Transport Aircraft ◽  
Fuzzy Logic Algorithm ◽  
Modeling Process ◽  
Data Points

This paper presents a modeling method based on a fuzzy-logic algorithm to establish aerodynamic models by using the datasets from flight data recorder (FDR). The fuzzy-logic aerodynamic models are utilized to estimate more accurately the nonlinear unsteady aerodynamics for a transport aircraft, including the effects of atmospheric turbulence. The main objective in this paper is to present the model development and the resulting models with continuous differentiability. The uncertainty and correlation of the data points are estimated and improved by monitoring a multivariable correlation coefficient in the modeling process. The latter is increased by applying a least square method to a set of data points to train a set of modeling coefficients. A commercial transport aircraft encountered severe atmospheric turbulence twice at transonic flight in descending phase is the study case in the present paper. The robustness and nonlinear interpolation capability of the fuzzy-logic algorithm are demonstrated in predicting the degradation in performance and stability characteristics of this transport in severe atmospheric turbulence with sudden plunging motion.

A Simple Procedure for Pattern Pre-Recognition Based on Fuzzy Logic Analysis

1997 ◽  
Vol 05 (01) ◽  
pp. 31-45 ◽  
Author(s):  
Vilém Novák ◽  
Alessandro Zorat ◽  
Mario Fedrizzi
Keyword(s):  
Fuzzy Logic ◽  
Simple Procedure ◽  
Formal Theory ◽  
Narrow Sense ◽  
Fuzzy Logic Analysis

In this paper a simple procedure for pattern pre-recognition is presented. The task is to recognize whether a given pattern should be interesting for further analysis or not. The description of the procedure presented in this paper is based on formal theory of fuzzy logic in narrow sense so that the procedure – being general – can be used for many other purposes where patterns are to be recognized.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

The potential implementation of ‘DEGALANTIL’ using fuzzy logic analysis

2017 ◽  
Author(s):  
I Made Alan Priyatna ◽  
Luh Putu Eka Yani ◽  
Satria Robi Trisnanto ◽  
I Gusti Bagus Ngurah Eka Darmaputra ◽  
Anak Agung Kompiyang Ratih Maldini ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Analysis

Grey-Fuzzy Logic Based Approach in Multi-Response Optimization of Semi-Solid Forging of A356 Aluminium Alloy

2021 ◽  
Vol 1016 ◽  
pp. 1875-1881
Author(s):  
Rajkumar Ohdar ◽  
Niranjan Kumar Singh ◽  
Archana Kumari ◽  
Randhir Kumar
Keyword(s):  
Fuzzy Logic ◽  
Performance Characteristics ◽  
Al Alloy ◽  
Forging Process ◽  
Response Optimization ◽  
Optimal Setting ◽  
Semi Solid ◽  
Solid Forging ◽  
Fuzzy Logic Analysis ◽  
Grey Relational

This paper presents an effective approach for the optimization of the semi-solid forging process of A356 Al-alloy based on the orthogonal array with the grey relational analysis and fuzzy logic analysis. Through the grey-fuzzy logic analysis, the optimization of complicated multiple performance characteristics can be converted into the optimization of a single grey-fuzzy reasoning grade. In this semi-solid forging process of A356 Al-alloy, the forging process parameters, namely the forging temperature, percent deformation, and die temperature are optimized with considerations of multiple performance characteristics including the tensile strength and hardness. The experimental results for the optimal setting have shown that the above performance characteristics in the semi-solid forging process of A356 Al-alloy can be improved effectively together through this approach.

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