Fault Diagnosis of Bearings Based on KJADE and VNWOA-LSSVM Algorithm

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fault Diagnosis of Rolling Bearings Based on SURF algorithm

This paper proposed a new method for fault diagnosis of rolling bearings based on SURF (Speeded-Up Robust Features) algorithm, where two-dimension signal is used. Different from other classical 1-d signal processed methods, the proposed method transforms the 1-dimensional vibration signals into images, then image processed methods are utilized to analyze the image signal so as to reach the goal...

متن کامل

Fault diagnosis of gearboxes using LSSVM and WPT

This paper concentrates on a new procedure which experimentally recognises gears and bearings faults of a typical gearbox system using a least square support vector machine (LSSVM). Two wavelet selection criteria Maximum Energy to Shannon Entropy ratio and Maximum Relative Wavelet Energy are used and compared to select an appropriate wavelet for feature extraction. The fault diagnosis method co...

متن کامل

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC

Abstract: This study proposes a novel fault diagnosis method that is based on empirical wavelet transform (EWT) and kernel density estimation classifier (KDEC), which can well diagnose fault type of the rolling element bearings. With the proposed fault diagnosis method, the vibration signal of rolling element bearing was firstly decomposed into a series of F modes by EWT, and the root mean squa...

متن کامل

Fault Detection of Bearings Using a Rule-based Classifier Ensemble and Genetic Algorithm

This paper proposes a reduct construction method based on discernibility matrix simplification. The method works with genetic algorithm. To identify potential problems and prevent complete failure of bearings, a new method based on rule-based classifier ensemble is presented. Genetic algorithm is used for feature reduction. The generated rules of the reducts are used to build the candidate base...

متن کامل

AN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS

In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Mathematical Problems in Engineering

سال: 2019

ISSN: 1024-123X,1563-5147

DOI: 10.1155/2019/8784154