A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot
Process monitoring is an important research problem in numerous areas. This paper proposes a novel process monitoring scheme by integrating the recurrence plot (RP) method and the control chart technique. Recently, the RP method has emerged as an effective tool to analyze waveform signals. However,...
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doaj-81e6c6da92a04738ae879479510eb25d2020-11-24T23:16:17ZengMDPI AGEntropy1099-43002015-09-011796379639610.3390/e17096379e17096379A New Process Monitoring Method Based on Waveform Signal by Using Recurrence PlotCheng Zhou0Weidong Zhang1National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, ChinaNational Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, ChinaProcess monitoring is an important research problem in numerous areas. This paper proposes a novel process monitoring scheme by integrating the recurrence plot (RP) method and the control chart technique. Recently, the RP method has emerged as an effective tool to analyze waveform signals. However, unlike the existing RP methods that employ recurrence quantification analysis (RQA) to quantify the recurrence plot by a few summary statistics; we propose new concepts of template recurrence plots and continuous-scale recurrence plots to characterize the waveform signals. A new feature extraction method is developed based on continuous-scale recurrence plot. Then, a monitoring statistic based on the top- approach is constructed from the continuous-scale recurrence plot. Finally, a bootstrap control chart is built to detect the signal changes based on the constructed monitoring statistics. The comprehensive simulation studies show that the proposed monitoring scheme outperforms other RQA-based control charts. In addition, a real case study of progressive stamping processes is implemented to further evaluate the performance of the proposed scheme for process monitoring.http://www.mdpi.com/1099-4300/17/9/6379process monitoringrecurrence plotbootstrapcontrol chart |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Cheng Zhou Weidong Zhang |
spellingShingle |
Cheng Zhou Weidong Zhang A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot Entropy process monitoring recurrence plot bootstrap control chart |
author_facet |
Cheng Zhou Weidong Zhang |
author_sort |
Cheng Zhou |
title |
A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot |
title_short |
A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot |
title_full |
A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot |
title_fullStr |
A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot |
title_full_unstemmed |
A New Process Monitoring Method Based on Waveform Signal by Using Recurrence Plot |
title_sort |
new process monitoring method based on waveform signal by using recurrence plot |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2015-09-01 |
description |
Process monitoring is an important research problem in numerous areas. This paper proposes a novel process monitoring scheme by integrating the recurrence plot (RP) method and the control chart technique. Recently, the RP method has emerged as an effective tool to analyze waveform signals. However, unlike the existing RP methods that employ recurrence quantification analysis (RQA) to quantify the recurrence plot by a few summary statistics; we propose new concepts of template recurrence plots and continuous-scale recurrence plots to characterize the waveform signals. A new feature extraction method is developed based on continuous-scale recurrence plot. Then, a monitoring statistic based on the top- approach is constructed from the continuous-scale recurrence plot. Finally, a bootstrap control chart is built to detect the signal changes based on the constructed monitoring statistics. The comprehensive simulation studies show that the proposed monitoring scheme outperforms other RQA-based control charts. In addition, a real case study of progressive stamping processes is implemented to further evaluate the performance of the proposed scheme for process monitoring. |
topic |
process monitoring recurrence plot bootstrap control chart |
url |
http://www.mdpi.com/1099-4300/17/9/6379 |
work_keys_str_mv |
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_version_ |
1725587884397821952 |