Locality preserving randomized canonical correlation analysis for real-time nonlinear process monitoring

2021 ◽  
Vol 147 ◽  
pp. 1088-1100
Author(s):  
Ping Wu ◽  
Xujie Zhang ◽  
Jiajun He ◽  
Siwei Lou ◽  
Jinfeng Gao
Keyword(s):  
Correlation Analysis ◽  
Real Time ◽  
Process Monitoring ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Nonlinear Process ◽  
Locality Preserving ◽  
Nonlinear Process Monitoring

Real-time damage detection of degrading systems

2019 ◽  
Vol 19 (3) ◽  
pp. 810-837 ◽  
Author(s):  
Tapas Tripura ◽  
Basuraj Bhowmik ◽  
Vikram Pakrashi ◽  
Budhaditya Hazra
Keyword(s):  
Correlation Analysis ◽  
Damage Detection ◽  
Real Time ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Degree Of Freedom ◽  
Time Varying ◽  
Analysis Algorithm ◽  
Stiffness Reduction ◽  
The Impact

In this article, a robust output-only real-time damage detection technique for multi-degree-of-freedom degrading systems using recursive canonical correlation analysis is presented. It has been observed that the impact of damage to a vibrating system gradually advances with time that sustains until the system degrades up to a considerable extent. Of significant interest is the effect of sudden damage in presence of continuous degradation in real-time, which is studied in the form of a sudden stiffness reduction in a separate floor. The proposed recursive canonical correlation analysis algorithm estimates the iterative update of eigenspace at each instant from the response data, thereby capturing the features of a time varying degrading structure in an online framework. Furthermore, recursive canonical correlation analysis algorithm is shown to reduce the computational cost by updating the eigenspace at each instant of time. This article explores newly developed recursive condition indicators: recursive Mahalanobis distance and recursive Itakura distance that elicit damage information from the eigenspace. In order to model degradation, simulations aimed at successfully capturing the behavior of the process in real-time becomes imperative. A general stochastic formulation of the coupled response-degradation problem accounting for the evolution of degradation is presented in the light of stiffness degradation problems. The evolution of time varying system responses is generated using a newly proposed Ito–Taylor expansion-based stochastic numerical integration formulation. Numerically simulated structural vibrating systems, namely, 2-degree-of-freedom base-isolated and 4-degree-of-freedom linear systems, have been used to check the performance of the recursive canonical correlation analysis method. The spatial damage detectability of the algorithm in real-time is explored through identifying crack location on a beam traversed by a vehicle. Finally, an experimental case study has been carried out to verify the robustness of the proposed algorithm. The identification results for both numerical and experimental cases demonstrate the efficacy of the proposed algorithm in identification of nonlinear and time varying behavior associated with degrading structural systems.

scholarly journals Real time vision/sensor based features processing for efficient HCI employing canonical correlation analysis

2016 ◽  
Vol 2 (4) ◽  
pp. 187-195
Author(s):  
Ehab H. El-Shazly ◽  
Moataz M. Abdelwahab ◽  
Atsushi Shimada ◽  
Rin-ichiro Taniguchi
Keyword(s):  
Correlation Analysis ◽  
Real Time ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Vision Sensor
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