scholarly journals Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Meng-Hui Wang ◽  
Pi-Chu Wu
Keyword(s):  
Genetic Algorithm ◽  
Fault Diagnosis ◽  
Experimental Results ◽  
Classification Methods ◽  
Recognition Method ◽  
Important Work ◽  
Industrial Apparatus ◽  
Fault Recognition ◽  
Traditional Classification ◽  
Hidden Fault

Due to the passenger’s security, the recognized hidden faults in car engines are the most important work for a maintenance engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel fault recognition method based on the genetic algorithm (GA) and the extension theory and also apply this method to the fault recognition of a practical car engine. The proposed recognition method has been tested on the Nissan Cefiro 2.0 engine and has also been compared to other traditional classification methods. Experimental results are of great effect regarding the hidden fault recognition of car engines, and the proposed method can also be applied to other industrial apparatus.

Interactive Sketch Design Recognition System Using Evolutionary Techniques

2014 ◽  
Vol 18 (1) ◽  
pp. 89-103
Author(s):  
P. Y. Mok ◽  
X.X. Wang ◽  
J. Xu ◽  
J.T. Fan ◽  
Y.L. Kwok ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Subjective Evaluation ◽  
Recognition System ◽  
Experimental Results ◽  
Fashion Design ◽  
Recognition Method ◽  
Sketch Recognition ◽  
Interactive Genetic Algorithm ◽  
Recognition Process ◽  
Composite Description

In this study, a methodology integrating a sketch design recognition approach with an interactive genetic algorithm is proposed to help laypersons get clothes reflecting their preferences. The sketch design recognition approach consists of a composite description model, a sketch recognition method and a database. First, a composite description model based on the knowledge of fashion design is developed to describe the characteristics of a skirt. Second, a sketch recognition method is used to help laypersons get satisfactory clothes. Third, a database in constructed to record general elements of skirts. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch recognition process. The experimental results demonstrate that the proposed method can 'recognize' users' preferred styles efficiently. The subjective evaluation has shown that the system can help general consumers without any fashion design or sketch training to create their own designs.

Power Transform Fault Diagnosis Based on the Adaptive Mutation Particle Swarm Optimization

2013 ◽  
Vol 756-759 ◽  
pp. 3804-3808
Author(s):  
Zhi Mei Duan ◽  
Jia Tang Cheng
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Power Transformer ◽  
Recognition Rate ◽  
Particle Swarm ◽  
Adaptive Mutation ◽  
Bp Network ◽  
Swarm Optimization ◽  
Fault Recognition

In order to improve the accuracy of fault diagnosis of power transformer, in this paper, a method is proposed that optimize the weight of BP neural network by adaptive mutation particle swarm optimization (AMPSO). According to the characteristic of transformer fault, the optimized neural network is used to diagnose fault of the power transformer. Individual particles action is amended by this algorithm and local minima problems of the standard PSO and BP network are overcooked. The experimental results show that, the method can classify transformer faults, and effectively improve the fault recognition rate.

Analog Circuits Fault Diagnosis Using Multifractal Analysis

2013 ◽  
Vol 721 ◽  
pp. 367-371
Author(s):  
Yong Kui Sun ◽  
Zhi Bin Yu
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Analog Circuits ◽  
Multifractal Analysis ◽  
Multifractal Spectrum ◽  
Experimental Results ◽  
Support Vector ◽  
Diagnosis Accuracy ◽  
Circuit Under Test

Analog circuits fault diagnosis using multifractal analysis is presented in this paper. The faulty response of circuit under test is analyzed by multifratal formalism, and the fault feature consists of multifractal spectrum parameters. Support vector machine is used to identify the faults. Experimental results prove the proposed method is effective and the diagnosis accuracy reaches 98%.

Application of Immune Genetic Algorithm in Survey Data Processing

2012 ◽  
Vol 241-244 ◽  
pp. 1737-1740
Author(s):  
Wei Chen
Keyword(s):  
Genetic Algorithm ◽  
Immune System ◽  
Data Processing ◽  
Survey Data ◽  
Heuristic Algorithm ◽  
Experimental Results ◽  
Immune Genetic Algorithm ◽  
Basic Principles ◽  
Immune Operator ◽  
Biological Immune System

The immune genetic algorithm is a kind of heuristic algorithm which simulates the biological immune system and introduces the genetic operator to its immune operator. Conquering the inherent defects of genetic algorithm that the convergence direction can not be easily controlled so as to result in the prematureness；it is characterized by a better global search and memory ability. The basic principles and solving steps of the immune genetic algorithm are briefly introduced in this paper. The immune genetic algorithm is applied to the survey data processing and experimental results show that this method can be practicably and effectively applied to the survey data processing.

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