Fault diagnosis method based on minimum entropy deconvolution and fruit fly optimization algorithm

2016 ◽  
Author(s):  
Jingsheng Jiang ◽  
Huaqing Wang ◽  
Gang Tang ◽  
Liuyang Song ◽  
Peng Chen
Keyword(s):  
Fault Diagnosis ◽  
Optimization Algorithm ◽  
Fruit Fly ◽  
Fruit Fly Optimization Algorithm ◽  
Minimum Entropy ◽  
Fruit Fly Optimization ◽  
Diagnosis Method

scholarly journals Fault diagnosis using improved pattern spectrum and fruit fly optimization algorithm–support vector machine

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401881093 ◽  
Author(s):  
Bing Wang ◽  
Xiong Hu ◽  
Wei Wang ◽  
Dejian Sun
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Optimization Algorithm ◽  
Simulation Analysis ◽  
Roller Bearing ◽  
Fruit Fly ◽  
Support Vector ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization ◽  
Pattern Spectrum

A fault diagnosis method using improved pattern spectrum and fruit fly optimization algorithm–support vector machine is proposed. Improved pattern spectrum is introduced for feature extraction by employing morphological erosion operator. Simulation analysis is processed, and the improved pattern spectrum curves present a steady distinction feature and smaller calculating amount than pattern spectrum method. Support vector machine with fruit fly optimization algorithm which can help seeking optimal parameters is employed for pattern recognition. Experiments were conducted, and the proposed method is verified by roller bearing vibration data including different fault types. The classification accuracy of the proposed approach reaches 87.5% (21/24) in training and 91.7% (44/48) in testing, showing an acceptable diagnosis effect.

Research on Enhancement Technology of Conveyor Belt Fault Images Based on Fruit Fly Optimization Algorithm

2014 ◽  
Vol 8 (1) ◽  
pp. 685-689
Author(s):  
Chunqing Ye ◽  
Changyun Miao ◽  
Xianguo Li ◽  
Yanli Yang
Keyword(s):  
Optimization Algorithm ◽  
Detection System ◽  
Fruit Fly ◽  
Conveyor Belt ◽  
Recognition Algorithm ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization ◽  
Wire Ropes ◽  
Fault Recognition ◽  
Steel Cord

In this research, we studied the fault recognition algorithm of steel cord conveyor belt, and obtained the wire ropes image by adopting the detection system of steel cord conveyor belt, so that the fault recognition algorithm of steel cord conveyor belt was proposed based on Fruit fly optimization algorithm. As we know that the fruit fly optimization algorithm is used for fault detection of the processing steel cord conveyor belt image and for obtaining the fault image. In the MATLAB environment, the algorithm process was designed and verified in terms of the effectiveness and accuracy. The experimental results show that with fast speed and high accuracy in detecting the fault image of steel cord conveyor belt rapidly and accurately, and in classifying scratch from fracture the proposed algorithm is suitable for the fault recognition of steel cord conveyor belt automatically.

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