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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Main Authors: Cheng Zhou, Weidong Zhang
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:Entropy
Subjects:
Online Access:http://www.mdpi.com/1099-4300/17/9/6379
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spelling 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
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