scholarly journals Model-independent time-delay interferometry based on principal component analysis

2021 ◽  
Vol 104 (12) ◽  
Author(s):  
Quentin Baghi ◽  
John Baker ◽  
Jacob Slutsky ◽  
James Ira Thorpe
Keyword(s):  
Principal Component Analysis ◽  
Time Delay ◽  
Principal Component ◽  
Component Analysis ◽  
Model Independent

scholarly journals Monitoring of Nonlinear Time-Delay Processes Based on Adaptive Method and Moving Window

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yunpeng Fan ◽  
Wei Zhang ◽  
Yingwei Zhang
Keyword(s):  
Principal Component Analysis ◽  
Time Delay ◽  
Principal Component ◽  
Component Analysis ◽  
Adaptive Method ◽  
Kernel Principal Component Analysis ◽  
Moving Window ◽  
Data Space ◽  
Weighted Principal Component ◽  
Adaptive Kernel

A new adaptive kernel principal component analysis (KPCA) algorithm for monitoring nonlinear time-delay process is proposed. The main contribution of the proposed algorithm is to combine adaptive KPCA with moving window principal component analysis (MWPCA) algorithm, and exponentially weighted principal component analysis (EWPCA) algorithm respectively. The new algorithm prejudges the new available sample with MKPCA method to decide whether the model is updated. Then update the KPCA model using EWKPCA method. And also extend MPCA and EWPCA from linear data space to nonlinear data space effectively. Monitoring experiment is performed using the proposed algorithm. The simulation results show that the proposed method is effective.

Using a single sensor for bridge condition monitoring via moving embedded principal component analysis

2020 ◽  
pp. 147592172098051
Author(s):  
Zhenhua Nie ◽  
Zhaofeng Shen ◽  
Jun Li ◽  
Hong Hao ◽  
Yizhou Lin ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Time Delay ◽  
State Space ◽  
Structural Damage ◽  
Damage Index ◽  
Principal Component ◽  
Component Analysis ◽  
The State ◽  
Contribution Ratio ◽  
Recorded Data

This article presents a novel data-driven structural damage detection method named moving embedded principal component analysis to monitor the bridge condition and detect the damage occurrence using only one sensor. A fixed moving window is used to cut out the time series of the recorded data for the analysis. The data set inside the window is embedded to be a multidimensional state space using time delay method. The matrix of the state space is analyzed using the standard principal component analysis method, and a novel damage index Rj defined with the eigenvalue is proposed to identify structural damage occurrence. The window length is determined by a new approach through examining the convergent spectrum of the contribution ratio of the first principal component of the embedded state space. The time delay is determined by the autocorrelation function of the response, and the embedding dimension is obtained by the cumulative contribution ratio of the state space. The windowed damage index can be calculated continuously by moving the window along the recorded vibration data. To demonstrate the performance of the proposed method, responses of a beam bridge model subjected to stochastic loads obtained with numerical simulations and experimental tests are analyzed to monitor the structural conditions. The results demonstrate that the proposed method can accurately identify the occurrence of damage and the abnormal behavior of the structure. The recorded data on a large suspension bridge are also analyzed. The analysis successfully identified an incident on this bridge when it was slightly scraped by the mast of a sand ship. This further verifies the effectiveness of the proposed method.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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