The Condition Monitoring of Large Slewing Bearing Based on Oil Analysis Method

2011 ◽  
Vol 474-476 ◽  
pp. 716-719 ◽  
Author(s):  
Xiu Qin Bai ◽  
Han Liang Xiao ◽  
Lu Zhang
Keyword(s):  
Special Kind ◽  
Rolling Bearing ◽  
Vibration Monitoring ◽  
Spectrometric Analysis ◽  
Analysis Method ◽  
Heavy Load ◽  
Slewing Bearing ◽  
Rolling Elements ◽  
Slewing Bearings ◽  
Wear Condition

Large slewing bearing is a special kind of rolling bearing with heavy load and very low rotation speed. It is important to carry out faults monitoring on this kind of rolling bearing. However, it is difficult to carry out vibration monitoring on such large slewing bearing. The running conditions of slewing bearings of ship loader and stacking crane in Qinghuangdao Port were analyzed using ferrography and spectrometric analysis technology. Monitoring results showed that the slewing bearing of SL-Q1 ship loader was under abnormal wear condition. Further inspection indicated that the rolling elements of this bearing underwent severe wear and broke down. This suggested that it was feasible to evaluating the wear conditions of this type of large low-speed heavy-load rolling bearing using ferrography and spectrometric analysis.

scholarly journals Influence of finite element mesh size on the carrying capacity analysis of single-row ball slewing bearing

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110090
Author(s):  
Peiyu He ◽  
Qinrong Qian ◽  
Yun Wang ◽  
Hong Liu ◽  
Erkuo Guo ◽  
...  
Keyword(s):  
Finite Element ◽  
Carrying Capacity ◽  
Mesh Size ◽  
Finite Element Mesh ◽  
Fe Model ◽  
Element Mesh ◽  
Heavy Load ◽  
Slewing Bearing ◽  
Maximum Contact ◽  
Slewing Bearings

Slewing bearings are widely used in industry to provide rotary support and carry heavy load. The load-carrying capacity is one of the most important features of a slewing bearing, and needs to be calculated cautiously. This paper investigates the effect of mesh size on the finite element (FE) analysis of the carrying capacity of slewing bearings. A local finite element contact model of the slewing bearing is firstly established, and verified using Hertz contact theory. The optimal mesh size of finite element model under specified loads is determined by analyzing the maximum contact stress and the contact area. The overall FE model of the slewing bearing is established and strain tests were performed to verify the FE results. The effect of mesh size on the carrying capacity of the slewing bearing is investigated by analyzing the maximum contact load, deformation, and load distribution. This study of finite element mesh size verification provides an important guidance for the accuracy and efficiency of carrying capacity of slewing bearings.

Effect of high-strength bolts and supporting structures on the carrying capacity of three-row roller slewing bearings

2020 ◽  
pp. 095440622094958
Author(s):  
Peiyu He ◽  
Yun Wang
Keyword(s):  
Carrying Capacity ◽  
Large Scale ◽  
High Strength ◽  
Element Model ◽  
Heavy Load ◽  
Slewing Bearing ◽  
Bolt Preload ◽  
Core Components ◽  
Slewing Bearings ◽  
Supporting Structures

Three-row roller slewing bearings are the core components of large-scale rotating equipment. A large structural size and heavy load conditions require an extremely high carrying capacity. The inner ring of the slewing bearing is divided into upper and lower parts in this paper, which is the same as the actual working condition and effectively avoids the increase in the stiffness caused by simplifying the inner ring as a whole. Different bolt models and bolt preloads, the effect of the roller diameter on the stiffness and the strength of the support structure are analysed to improve the calculation accuracy and efficiency of the carrying capacity of the slewing bearing. Calculation formulas based on engineering experience and strain measurement are used to verify the validity of the finite element model. The research shows that the carrying capacity of the slewing bearing is affected by the supporting structure; as the bolt preload increases, the overall deformation of the slewing bearing decreases, and the load distribution is smoother. The key structures of the slewing bearing are studied, which is conducive to improving the carrying capacity and optimizing the design.

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

A Clustering-Based Framework for Performance Degradation Prediction of Slewing Bearing Using Multiple Physical Signals

2019 ◽  
Vol 5 (2) ◽  
Author(s):  
Peng Ding ◽  
Hua Wang ◽  
Yongfen Dai
Keyword(s):  
Degradation Process ◽  
Remaining Useful Life ◽  
Data Driven ◽  
Self Organizing Map ◽  
Rolling Bearings ◽  
Heavy Load ◽  
Joint Application ◽  
Learning Modes ◽  
Useful Life ◽  
Slewing Bearings

Diagnosing the failure or predicting the performance state of low-speed and heavy-load slewing bearings is a practical and effective method to reduce unexpected stoppage or optimize the maintenances. Many literatures focus on the performance prediction of small rolling bearings, while studies on slewing bearings' health evaluation are very rare. Among these rare studies, supervised or unsupervised data-driven models are often used alone, few researchers devote to remaining useful life (RUL) prediction using the joint application of two learning modes which could fully take diversity and complexity of slewing bearings' degradation and damage into consideration. Therefore, this paper proposes a clustering-based framework with aids of supervised models and multiple physical signals. Correlation analysis and principle component analysis (PCA)-based multiple sensitive features in time-domain are used to establish the performance recession indicators (PRIs) of torque, temperature, and vibration. Subsequently, these three indicators are divided into several parts representing different degradation periods via optimized self-organizing map (OSOM). Finally, corresponding data-driven life models of these degradation periods are generated. Experimental results indicate that multiple physical signals can effectively describe the degradation process. The proposed clustering-based framework is provided with a more accurate prediction of slewing bearings' RUL and well reflects the performance recession periods.

Diagnosis Research on Main Bearing Wear of Gasoline Engines in Mechanical Engineering

2013 ◽  
Vol 644 ◽  
pp. 304-307 ◽  
Author(s):  
Chang Shun Wang
Keyword(s):  
Gasoline Engine ◽  
Vibration Monitoring ◽  
Analysis Method ◽  
Characteristic Parameters ◽  
Main Bearing ◽  
Vibration Signals ◽  
Gasoline Engines ◽  
Test Spot ◽  
Monitoring Mechanism ◽  
Spectral Analysis Method

The different clearances of main bearing of previously designed on EQ6100 model gasoline engine is diagnosed by means of vibration monitoring mechanism. Breakdown signals of main test on different speed, clearance of main bearing, test spot and weather were analyzed by Spectral Analysis method and compared with normal and abnormal vibration signals. As a result, the characteristic parameters and the identifying methods of breakdown are given. In addition, the problems of fault detection are pointed out.

Noise calculation method of deep groove ball bearing caused by vibration of rolling elements considering raceway waviness

2021 ◽  
pp. 095440622110458
Author(s):  
Minjie Sun ◽  
Haojie Xu ◽  
Qi An
Keyword(s):  
Ball Bearing ◽  
Axial Direction ◽  
Rolling Bearing ◽  
Mechanical Analysis ◽  
Machining Accuracy ◽  
Surface Waviness ◽  
Random Surface ◽  
Deep Groove ◽  
Deep Groove Ball Bearing ◽  
Rolling Elements

Raceway waviness error is the main reason to cause rolling elements to vibrate along axial direction and emit noise. In this paper, the mechanical analysis on deep groove ball bearing is carried out. With auto-correlation function, random surface waviness of both inner and outer raceways is simulated. A contact model of rolling elements and raceways considering surface waviness is established. Combining with the theory of acoustic equation, a calculation model is established for the noise caused by vibration of rolling elements and inner ring. The results show that with the decrease of machining accuracy, the noise of rolling elements increases due to axial vibration; with the increase of rotation speed, the noise also increases. Besides, the spectrum of radiation noise of inner raceway with different waviness amplitudes is given. The results indicate that the 3-D waviness on raceway surface has an influence on the vibration and the noise emitted by both rolling elements and inner ring, and provide guidance for sound control in deep groove rolling bearing.

Dynamic Interactions Between the Rolling Element and the Cage in Rolling Bearing Under Rotational Speed Fluctuation Conditions

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Wenbing Tu ◽  
Ya Luo ◽  
Wennian Yu
Keyword(s):  
Dynamic Model ◽  
Rotational Speed ◽  
Rolling Bearing ◽  
Nonlinear Dynamic Model ◽  
Dynamic Interactions ◽  
Interaction Forces ◽  
Rolling Element ◽  
Speed Fluctuation ◽  
Rolling Elements ◽  
Fluctuation Frequency

Abstract A nonlinear dynamic model is proposed to investigate the dynamic interactions between the rolling element and cage under rotational speed fluctuation conditions. Discontinuous Hertz contact between the rolling element and the cage and lubrication and interactions between rolling elements and raceways are considered. The dynamic model is verified by comparing simulation result with the published experimental data. Based on this model, the interaction forces and the contact positions between the rolling element and the cage with and without the rotational speed fluctuation are analyzed. The effects of fluctuation amplitude, fluctuation frequency, and cage pocket clearance on the interaction forces between the rolling element and the cage are also investigated. The results show that the fluctuation of the rotational speed and the cage pocket clearance significantly affects the interaction forces between the rolling element and the cage.

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