bearing performance degradation assessment using

[PDF] Performance Degradation Assessment of Rolling

Performance degradation assessment of rolling element bearings is vital for the reliable and cost-efficient operation and maintenance of rotating machines especially for the implementation of condition-based maintenance (CBM) For robust degradation assessment of rolling element bearings uncertainties such as those induced from usage variations or sensor errors must be taken into account

Bearing Performance Degradation Assessment Using

Bearing Performance Degradation Assessment Using Linear Discriminant Analysis and Coupled HMM T Liu∗ 1 J Chen X N Zhou1 and W B Xiao2 1 State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai 200240 P R China 2 Shanghai Institute of Satellite Engineering Shanghai 200240 P R China E-mail address: Liutao_shsjtu edu cn (T Liu)

Degradation assessment and trend prediction of

It is of significance to monitor the operating status of rolling bearings In order to obtain degradation of bearing performance timely and predict its trend this paper proposed a bearing health state assessment method based on Mahalanobis distance metric and a prediction method based on echo state network By designing degradation experiment and applying the proposed method to analyze the

A monotonic degradation assessment index of rolling

Performance degradation assessment based on condition monitoring plays an important role in ensuring reliable operation of equipment reducing production downtime and saving maintenance costs yet performance degradation has strong fuzziness and the dynamic information is random and fuzzy making it a challenge how to assess the fuzzy bearing

Bearing Performance Degradation Assessment Using

Bearing is one of the most important units in rotary machinery its performance may vary significantly under different working stages Thus it is critical to choose the most effective features for bearing performance degradation prediction Linear Discriminant Analysis (LDA) is a useful method in finding few feature's dimensions that best discriminate a set of features extracted from original

Machine Performance Degradation Assessment and

Pan Y Chen J Li X (2010) Bearing performance degradation assessment based on lifting wavelet packet decomposition and fuzzy c-means Mech Syst Signal Process 24:559–566 CrossRef Google Scholar 13 Liao H Zhao W Guo H (2006) Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model

Assessment of bearing performance degradation via

As a key component in rotating machinery the operating reliability of bearing influences the performance and service life of the equipment directly In order to describe bearing performance degradation (BPD) process effectively an assessment approach combining extension and ensemble empirical mode decomposition (EEMD) was proposed First the extension was utilized to construct the matter

Roller Bearing Performance Degradation Assessment

This paper presents a new method to assess the performance degradation of roller bearings based on the fusion of multiple features with the aim of improving the early degradation detection ability of the electrostatic monitoring system At first a set of feature parameters of the electrostatic monitoring system indicating the normal state of the bearings are extracted from the perspective of

Solid lubricated bearings performance degradation

Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics Journal of Sound and Vibration 2007 302 (4–5): 951–61 20 Pan Y Chen J Guo L Robust bearing performance degradation assessment method based on improved wavelet packet-support vector data description

A Feature Extraction Method for Vibration Signal of

2016-6-8cyclic spectral analysis method for bearing performance degradation assessment [6] Fatima et al classified faults and unbalance using support vector machines (SVMs) and provided a classification of 75 % or better [7] Shen et al developed a parameterized Doppler distorted model by which bearing faults can be successfully detected from the

Rolling Element Bearing Performance Degradation

2019-7-30By focusing on the issue of rolling element bearing (REB) performance degradation assessment (PDA) a solution based on variational mode decomposition (VMD) and Gath-Geva clustering time series segmentation (GGCTSS) has been proposed

Solid lubricated bearings performance degradation

Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics Journal of Sound and Vibration 2007 302 (4–5): 951–61 20 Pan Y Chen J Guo L Robust bearing performance degradation assessment method based on improved wavelet packet-support vector data description

Performance Degradation Assessment for Bearing

This paper proposes a novel performance degradation assessment method for bearing based on ensemble empirical mode decomposition (EEMD) and Gaussian mixture model (GMM) EEMD is applied to preprocess the nonstationary vibration signals and get the feature space

[PDF] Performance Degradation Assessment of Rolling

Performance degradation assessment of rolling element bearings is vital for the reliable and cost-efficient operation and maintenance of rotating machines especially for the implementation of condition-based maintenance (CBM) For robust degradation assessment of rolling element bearings uncertainties such as those induced from usage variations or sensor errors must be taken into account

Performance degradation assessment of rolling

2020-6-26To solve these problems a convolutional neural network and deep long-short term memory (CNN-DLSTM) based architecture is proposed to obtain an unsupervised H-statistic for performance degradation assessment of rolling bearing using sensor time-series data Firstly a CNN is applied to extract local abstract features from raw sensor data

A Method for Evaluating Performance Degradation of Rolling

A quantitative index for evaluating the performance degradation characteristic is designed based on the physical characteristics of the performance degradation curve and a calculation process of the evaluation index is given by using the method of detecting time

Performance Degradation Assessment of Rolling

Rolling element bearings are an important unit in the rotating machines and their performance degradation assessment is the basis of condition-based maintenance Targeting the non-linear dynamic characteristics of faulty signals of rolling element bearings a bearing performance degradation assessment approach based on improved fuzzy entropy (FuzzyEn) is proposed in this paper

Performance degradation assessment of rolling

Downloadable (with restrictions)! Many traditional approaches for performance degradation assessment of rolling bearings using sensor data make assumptions about how they degrade or fault evolve However the sequential sensor data cannot be directly taken as input in the traditional models since the data always contain noise and change in length

Assessment Method for Rolling Bearing Performance

Abstract Rolling bearing performance degradation assessment has been receiving much attention for which itscrucial role to realize CBM(condition-based maintenance) This paper proposed a novel bearing performance degradation method based on TESPAR(Time Encoded Signal Processing and Recognition)and GMM(Gauss Mixture Model)

Research on Performance Degradation Assessment

2016-11-1Performance degradation assessment of rollling bearing SVDD SVDD Sphere Modell SVDD Distance SVDD Model Original data of normal rolling bearing Feature Extraction Data to be tested Figure 1 Main steps of bearing performance degradation assessment radius R to enclose most of the objects as shown in (1) Minimize 2 1 ( ) N pF i i ORa R c[[ (1)

Figure 8 from Performance Degradation Assessment

DOI: 10 3390/e16105400 Corpus ID: 11641710 Performance Degradation Assessment of Rolling Element Bearings Based on an Index Combining SVD and Information Exergy article{Zhang2014PerformanceDA title={Performance Degradation Assessment of Rolling Element Bearings Based on an Index Combining SVD and Information Exergy} author={Bin Zhang and Lijun

Journal of Mechanical Engineering

2016-9-18Journal of Mechanical Engineering ›› 2017 Vol 53 ›› Issue (21): 181-189 doi: 10 3901/JME 2017 21 181 Previous Articles Next Articles Random Forest and Principle Components Analysis Based on Health Assessment Methodology for Tool Wear

Bearing Performance Degradation Assessment Using

Bearing performance degradation assessment is of great significance for proactive maintenance and near-zero downtime For this purpose a novel assessment method is proposed based on lifting wavelet packet symbolic entropy (LWPSE) and support vector data description (SVDD) LWPSE is presented for feature extraction by jointing use of lifting wavelet packet transform and symbolic entropy

Performance Degradation Assessment for Bearing

This paper proposes a novel performance degradation assessment method for bearing based on ensemble empirical mode decomposition (EEMD) and Gaussian mixture model (GMM) EEMD is applied to preprocess the nonstationary vibration signals and get the feature space

Journal of Mechanical Engineering

2016-9-18Journal of Mechanical Engineering ›› 2017 Vol 53 ›› Issue (21): 181-189 doi: 10 3901/JME 2017 21 181 Previous Articles Next Articles Random Forest and Principle Components Analysis Based on Health Assessment Methodology for Tool Wear

Bearing performance degradation assessment using

Home Browse by Title Periodicals Expert Systems with Applications: An International Journal Vol 38 No 6 Bearing performance degradation assessment using locality preserving projections research-article Bearing performance degradation assessment using locality preserving projections

Performance degradation assessment of rolling

For robust degradation assessment of rolling element bearings uncertainties such as those induced from usage variations or sensor errors must be taken into account This paper presents an information exergy index for bearing performance degradation assessment that combines singular value decomposition (SVD) and the information exergy method