Multivariate statistics process control for dimensionality reduction in structural assessment-Reference-Cited by-同舟云学术

Multivariate statistics process control for dimensionality reduction in structural assessment

Published:2008-01 Issue:1 Volume:22 Page:155-171
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Mujica L.E.,Vehí J.,Ruiz M.,Verleysen M.,Staszewski W.,Worden K.

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference42 articles.

1. Applied Multivariate Statistical Analysis. 0-130-41146-9;Johnson,1988

2. L. Smith, A tutorial on principal components analysis, Technical Report, University of Otago, New Zealand, February 2002.

3. Partial least-squares regression: a tutorial;Geladi;Analytica Chimica Acta,1986

4. Health Monitoring of Aerospace Structures: Smart Sensor Technologies and Signal Processing;Staszewski,2004

5. A summary review of vibration-based damage identification methods;Doebling;The Shock and Vibration Digest,1998

Cited by 62 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Low-Rank Tensor Completion for Heart Failure Exacerbation Detection in Multivariate Time Series with Missing Data;2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS);2024-06-26

2. Neighborhood component analysis to leverage the class label information during feature selection to enhance the damage classification performance;Structures;2023-11

3. Improving Long-Term Guided Wave Damage Detection With Measurement Resampling;IEEE Sensors Journal;2023-04-01

4. Water quality evaluation of Dahai Lake in Inner Mongolia based on improved Nemero pollution index method and principal component analysis;E3S Web of Conferences;2023

5. Challenges and opportunities of deep learning-based process fault detection and diagnosis: a review;Neural Computing and Applications;2022-11-18