Study and Analysis of On-Line Detection and Fault Diagnosis System of Rolling Bearing

2013 ◽  
Vol 443 ◽  
pp. 218-222
Author(s):  
Jing Zi Wei ◽  
Ran Zhang
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Rolling Bearing ◽  
Fault Detection And Diagnosis ◽  
Detection Methods ◽  
Line Detection ◽  
Diagnosis System ◽  
Bearing Fault ◽  
On Line ◽  
Fault Diagnosis System

This paper first of all gives an introduction to the structure of rolling bearing, development stage of fault and the main fault types; then, it makes an analysis of the common detection methods and the technologies involved in rolling bearing fault; at last, based on the emphasis on the rolling bearing on-line detection and fault diagnosis system of acoustic emission technology, it elaborates the basic principles of acoustic emission, rolling bearing fault detection and diagnosis system experiment setting. Meanwhile, it introduces modern signal processing technology into acoustic emission information feature extraction and state recognition, such as wavelet analysis and wavelet packet analysis.

scholarly journals A Denoising Autoencoder-Based Bearing Fault Diagnosis System for Time-Domain Vibration Signals

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yi Gu ◽  
Jiawei Cao ◽  
Xin Song ◽  
Jian Yao
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Rolling Bearing ◽  
Rolling Bearings ◽  
Bp Network ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Novel Approach ◽  
Fault Diagnosis System ◽  
Original Time

The condition monitoring of rotating machinery is always a focus of intelligent fault diagnosis. In view of the traditional methods’ excessive dependence on prior knowledge to manually extract features, their limited capacity to learn complex nonlinear relations in fault signals and the mixing of the collected signals with environmental noise in the course of the work of rotating machines, this article proposes a novel approach for detecting the bearing fault, which is based on deep learning. To effectively detect, locate, and identify faults in rolling bearings, a stacked noise reduction autoencoder is utilized for abstracting characteristic from the original vibration of signals, and then, the characteristic is provided as input for backpropagation (BP) network classifier. The results output by this classifier represent different fault categories. Experimental results obtained on rolling bearing datasets show that this method can be used to effectively diagnose bearing faults based on original time-domain signals.

The Developmental Research on Fault Diagnosis System of Mine Fan Based on Grey Theory

2011 ◽  
Vol 105-107 ◽  
pp. 656-659 ◽  
Author(s):  
Dong Chen Li
Keyword(s):  
Fault Diagnosis ◽  
Data Storage ◽  
Grey Theory ◽  
Developmental Research ◽  
Software Platform ◽  
Diagnosis System ◽  
Fault Monitoring ◽  
On Line ◽  
Fault Diagnosis System

The system uses GRAP in Grey Theory to conduct fault diagnosis of fan and chooses LabWEV for software platform, developing a set of system aiming at fault monitoring on line and diagnosis of mine fan in order to guarantee the running state of fan continuously and efficiently . This system has functions of monitoring on line,fault diagnosis,fault warning,data storage, history inquiry and so on.

MVC-2M Fault Diagnosis System and its Application

1991 ◽  
Author(s):  
G. P. Xu ◽  
W. Z. Lu ◽  
X. Q. Wu ◽  
W. X. Weng ◽  
N. M. Ge ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Machine Building ◽  
Measuring Instruments ◽  
Local Dynamic ◽  
Structural Dynamic ◽  
Diagnosis System ◽  
Power Stations ◽  
Structural Dynamic Characteristics ◽  
On Line ◽  
Fault Diagnosis System

The MVC-2M Fault Diagnosis System — an achievement of the national key research task in this field is presented in this article. The system can be used in various fields such as marine power engines, power generation, petrochemical industry, aviation and space, machine building etc. The basic functions of this system include real-time condition monitoring, on-line and off-line fault diagnosis, establishment of operation database, storage of fault data in blackbox, calibration of vibration measuring instruments, analysis of structural dynamic characteristics, local dynamic balancing, and so on. This article also presents several practical experieces during its term of service in Chinese naval vessels and power stations. It is widely confirmed that the MVC-2M system is essential to forecast the faults which probably would happen and thus is successful for avoiding the serious damage of the machines in motion.

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