scholarly journals Sequential Fuzzy Diagnosis Method for Motor Roller Bearing in Variable Operating Conditions Based on Vibration Analysis

Sensors ◽  
2013 ◽  
Vol 13 (6) ◽  
pp. 8013-8041 ◽  
Author(s):  
Ke Li ◽  
Xueliang Ping ◽  
Huaqing Wang ◽  
Peng Chen ◽  
Yi Cao
Keyword(s):  
Vibration Analysis ◽  
Roller Bearing ◽  
Operating Conditions ◽  
Diagnosis Method ◽  
Fuzzy Diagnosis ◽  
Variable Operating Conditions

Recent Progress of Vibration Analysis on Fault Diagnosis for Rolling Bearing

2011 ◽  
Vol 84-85 ◽  
pp. 544-547
Author(s):  
En Gao Peng ◽  
Zheng Lin Liu
Keyword(s):  
Fault Diagnosis ◽  
Vibration Analysis ◽  
Recent Progress ◽  
Roller Bearing ◽  
Rolling Bearing ◽  
Development Trend ◽  
Existing Problems ◽  
Detection Approach ◽  
Diagnosis Method ◽  
The Development Trend

Rolling bearing is extensively used in various areas including shipbuilding, aircraft, mining, manufacturing, agriculture, etc. The breakdowns of the bearings may do unexpected hazardous to the machinery. Therefore, it is crucial for engineers and researchers to monitor the bearing conditions in time in order to prevent the malfunctions of the plants. Hence the vibration analysis accompanying other condition monitoring methodologies has been successfully used in the field of roller bearings fault diagnosis as well as other key components. The fault diagnosis method of roller bearing using vibration analysis was introduced in this paper. And the development trend of vibration analysis was presented. Meanwhile the main existing problems in fault diagnosis of roller bearing were discussed. It concludes that the integration of vibration analysis and other detection approach can provide effective and reliable fault diagnosis results.

Fault Detection for Roller Bearing with Vibration Analysis and Information Fusion in Sorting Machine Induction

2014 ◽  
Vol 494-495 ◽  
pp. 805-808
Author(s):  
Wei Chen ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Si Cheng Nian
Keyword(s):  
Information Fusion ◽  
Vibration Analysis ◽  
High Speed ◽  
Roller Bearing ◽  
Vibration Signal ◽  
Operating Conditions ◽  
Independent Evidence ◽  
Sorting Machine ◽  
Metal Metal ◽  
Output Information

Due to continuous metal-metal contacts in heavy and high-speed operating conditions, sorting machine inductions roller bearing easily occurs malfunctions. Therefore, its crucial to make incipient fault diagnosis. This paper presents a novel diagnosis algorithm using vibration analysis and information fusion. In the algorithm, vibration signal for roller bearing is firstly analyzed. Then extracted fault features are used as input eigenvector of constructed neural network classifier. In order to improve diagnosis accuracy, take output information of each single classifier as independent evidence, and aggregate them using improved Dempsters combination rule. Experiment results show that proposed algorithm has high accuracy of 99.5%.

Investigations of Road Wear Caused by Studded Tires

2014 ◽  
Vol 42 (1) ◽  
pp. 2-15
Author(s):  
Johannes Gültlinger ◽  
Frank Gauterin ◽  
Christian Brandau ◽  
Jan Schlittenhard ◽  
Burkhard Wies
Keyword(s):  
Traffic Safety ◽  
Test Bench ◽  
Operating Conditions ◽  
Test Method ◽  
Analytical Models ◽  
The Road ◽  
Driving Speed ◽  
Major Factors ◽  
Tire Friction ◽  
Variable Operating Conditions

ABSTRACT The use of studded tires has been a subject of controversy from the time they came into market. While studded tires contribute to traffic safety under severe winter conditions by increasing tire friction on icy roads, they also cause damage to the road surface when running on bare roads. Consequently, one of the main challenges in studded tire development is to reduce road wear while still ensuring a good grip on ice. Therefore, a research project was initiated to gain understanding about the mechanisms and influencing parameters involved in road wear by studded tires. A test method using the institute's internal drum test bench was developed. Furthermore, mechanisms causing road wear by studded tires were derived from basic analytical models. These mechanisms were used to identify the main parameters influencing road wear by studded tires. Using experimental results obtained with the test method developed, the expected influences were verified. Vehicle driving speed and stud mass were found to be major factors influencing road wear. This can be explained by the stud impact as a dominant mechanism. By means of the test method presented, quantified and comparable data for road wear caused by studded tires under controllable conditions can be obtained. The mechanisms allow predicting the influence of tire construction and variable operating conditions on road wear.

Treatment system response to transient AOX (adsorbable organic halogen) loadings

1997 ◽  
Vol 35 (2-3) ◽  
pp. 85-91
Author(s):  
D. A. Barton ◽  
J. D. Woodruff ◽  
T. M. Bousquet ◽  
A. M. Parrish
Keyword(s):  
Paper Industry ◽  
Model Development ◽  
Operating Conditions ◽  
System Response ◽  
Additional Information ◽  
Organic Halogen ◽  
Aox Removal ◽  
Variable Operating Conditions ◽  
Plant Shutdown

If promulgated as proposed, effluent guidelines for the U.S. pulp and paper industry will impose average monthly and maximum daily numerical limits of discharged AOX (adsorbable organic halogen). At this time, it is unclear whether the maximum-day variability factor used to establish the proposed effluent guidelines will provide sufficient margin for mills to achieve compliance during periods of normal but variable operating conditions within the pulping and bleaching processes. Consequently, additional information is needed to relate transient AOX loadings with final AOX discharges. This paper presents a simplistic dynamic model of AOX decay during treatment. The model consists of hydraulic characterization of an activated sludge process and a first-order decay coefficient for AOX removal. Data for model development were acquired by frequent collection of influent and effluent samples at a bleach kraft mill during a bleach plant shutdown and startup sequence.

Applications of vibro-acoustic measurement and analysis in conjunction with tribological parameters to assess surface fatigue wear developed in the roller-bearing system

2021 ◽  
pp. 135065012098246
Author(s):  
Shashikant Pandey ◽  
Muniyappa Amarnath
Keyword(s):  
Roller Bearing ◽  
Operating Conditions ◽  
Rolling Contact ◽  
Stribeck Curve ◽  
Fatigue Wear ◽  
Surface Fatigue ◽  
Rolling Element ◽  
Measurement And Analysis ◽  
Contact Surfaces ◽  
Bearing System

Rolling-element bearings are the most commonly used components in all rotating machinery. The variations in the operating conditions such as an increase in the number of operating cycles, load, speed, service temperature, and lubricant degradation result in the development of various defects such as pitting, spalling, scuffing, scoring, etc. The defects that appeared on rolling contact surfaces cause surface deterioration and change in the vibration and sound levels of the bearing system. The present experimental investigations are aimed at assessing the surface fatigue wear that appears on the contact surfaces of roller bearings. The studies considered the estimation of specific film thickness, analysis of surface fatigue wear developed on the rolling-element surfaces, surface roughness analysis, grease degradation analysis using Fourier transform infrared radiation, and vibration and sound signal measurement and analysis. The results obtained from the experimental investigation provide a good correlation between surface wear, vibration, and sound signals with a transition in the lubrication regimes in the Stribeck curve.

Research on Roller Bearing with Fault Diagnosis Method Based on EMD and BP Neural Network

2014 ◽  
Vol 1014 ◽  
pp. 501-504 ◽  
Author(s):  
Shu Guo ◽  
You Cai Xu ◽  
Xin Shi Li ◽  
Ran Tao ◽  
Kun Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Roller Bearing ◽  
Vibration Signal ◽  
Classification Performance ◽  
Outer Race ◽  
Mode Decomposition ◽  
Diagnosis Method ◽  
Main Fault

In order to discover the fault with roller bearing in time, a new fault diagnosis method based on Empirical mode decomposition (EMD) and BP neural network is put forward in the paper. First, we get the fault signal through experiments. Then we use EMD to decompose the vibration signal into a series of single signals. We can extract main fault information from the single signals. The kurtosis coefficient of the single signals forms a feature vector which is used as the input data of the BP neural network. The trained BP neural network can be used for fault identification. Through analyzing, BP neural network can distinguish the fault into normal state, inner race fault, outer race fault. The results show that this method can gain very stable classification performance and good computational efficiency.

Sign in / Sign up

Export Citation Format

Share Document