Performance Degradation Analysis of Mechanical Seal Based on Vibration Signal Processing

2017 ◽  
Author(s):  
Di Liu ◽  
Shaoping Wang ◽  
Chao Zhang
Keyword(s):  
Signal Processing ◽  
Vibration Signal ◽  
Performance Degradation ◽  
Mechanical Seal ◽  
Degradation Analysis

Performance degradation analysis of solid lubricated bearings based on Laplace wavelet filter and self-organizing map

2013 ◽  
Vol 228 (10) ◽  
pp. 1743-1753 ◽  
Author(s):  
Chao Zhang ◽  
Shaoping Wang
Keyword(s):  
Feature Vector ◽  
Vibration Signal ◽  
Degradation Process ◽  
Performance Degradation ◽  
Friction Torque ◽  
Self Organizing Map ◽  
Wavelet Filter ◽  
Degradation Analysis ◽  
Space Mechanisms ◽  
Self Organizing

Solid lubricated bearings are commonly used in space mechanisms and other appliances, and their reliability analysis has drawn more and more attention. This paper focuses on the performance degradation analysis of solid lubricated bearings. Based on the vibration and friction torque signal of solid lubricated bearings, Laplace wavelet filter is adopted to process vibration signal and feature vector is constructed by calculating time-domain parameters of filtered vibration signal and original friction torque signal. Self-organizing map is then adopted to analyze the performance degradation based on extracted feature vectors. Experimental results show that this method can describe performance degradation process effectively.

scholarly journals HKF-SVR Optimized by Krill Herd Algorithm for Coaxial Bearings Performance Degradation Prediction

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 660 ◽  
Author(s):  
Fang Liu ◽  
Liubin Li ◽  
Yongbin Liu ◽  
Zheng Cao ◽  
Hui Yang ◽  
...  
Keyword(s):  
Kernel Method ◽  
Back Propagation ◽  
Vibration Signal ◽  
Back Propagation Neural Network ◽  
Industrial Applications ◽  
Performance Degradation ◽  
Support Vector ◽  
Krill Herd Algorithm ◽  
Krill Herd ◽  
Learning Machine

In real industrial applications, bearings in pairs or even more are often mounted on the same shaft. So the collected vibration signal is actually a mixed signal from multiple bearings. In this study, a method based on Hybrid Kernel Function-Support Vector Regression (HKF–SVR) whose parameters are optimized by Krill Herd (KH) algorithm was introduced for bearing performance degradation prediction in this situation. First, multi-domain statistical features are extracted from the bearing vibration signals and then fused into sensitive features using Kernel Joint Approximate Diagonalization of Eigen-matrices (KJADE) algorithm which is developed recently by our group. Due to the nonlinear mapping capability of the kernel method and the blind source separation ability of the JADE algorithm, the KJADE could extract latent source features that accurately reflecting the performance degradation from the mixed vibration signal. Then, the between-class and within-class scatters (SS) of the health-stage data sample and the current monitored data sample is calculated as the performance degradation index. Second, the parameters of the HKF–SVR are optimized by the KH (Krill Herd) algorithm to obtain the optimal performance degradation prediction model. Finally, the performance degradation trend of the bearing is predicted using the optimized HKF–SVR. Compared with the traditional methods of Back Propagation Neural Network (BPNN), Extreme Learning Machine (ELM) and traditional SVR, the results show that the proposed method has a better performance. The proposed method has a good application prospect in life prediction of coaxial bearings.

Rolling bearing degradation condition clustering using multidimensional degradation feature and Gath–Geva fuzzy clustering algorithm

2020 ◽  
pp. 107754632095495
Author(s):  
Bing Wang ◽  
Xiong Hu ◽  
Tao X Mei ◽  
Sun D Jian ◽  
Wang Wei
Keyword(s):  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Chaotic Map ◽  
Vibration Signal ◽  
Degradation Process ◽  
Rolling Bearing ◽  
Performance Degradation ◽  
Time Parameter ◽  
Mechanical Equipment ◽  
Time Dimension

In allusion to the issue of rolling bearing degradation feature extraction and degradation condition clustering, a logistic chaotic map is introduced to analyze the advantages of C0 complexity and a technique based on a multidimensional degradation feature and Gath–Geva fuzzy clustering algorithmic is proposed. The multidimensional degradation feature includes C0 complexity, root mean square, and curved time parameter which is more in line with the performance degradation process. Gath–Geva fuzzy clustering is introduced to divide different conditions during the degradation process. A rolling bearing lifetime vibration signal from intelligent maintenance system bearing test center was introduced for instance analysis. The results show that C0 complexity is able to describe the degradation process and has advantages in sensitivity and calculation speed. The introduced degradation indicator curved time parameter can reflect the agglomeration character of the degradation condition at time dimension, which is more in line with the performance degradation pattern of mechanical equipment. The Gath–Geva fuzzy clustering algorithmic is able to cluster degradation condition of mechanical equipment such as bearings accurately.

scholarly journals Baseband I/Q regeneration Method for Direct Conversion Receiver to nullify effect of I/Q mismatch

2016 ◽  
Vol 5 (3) ◽  
pp. 50 ◽  
Author(s):  
M. Shah ◽  
S. Gupta
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Low Power ◽  
Digital Signal ◽  
Direct Conversion ◽  
Performance Degradation ◽  
Wireless Receiver ◽  
Novel Method ◽  
The One

Direct Conversion Receiver is the choice of the today’s designer for low power compact wireless receiver. DCR is attractive due to low power, small size and highly monolithic integratable structure, but distortions affect its performance.  I/Q mismatch is the one of the major distortion which is responsible for performance degradation.  In this paper, a novel method for Direct Conversion Receiver is suggested, which makes it insensitive to the I/Q mismatch. Here the classical homodyne architecture is modified to nullify effect of I/Q mismatch. The proposed method can be implemented in the Digital Signal Processing (DSP) back-end section also.  This feature makes it acceptable in the already designed/functioning classical homodyne architecture based receiver.

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