Canonical Variate Residuals-Based Fault Diagnosis for Slowly Evolving Faults
This study puts forward a novel diagnostic approach based on canonical variate residuals (CVR) to implement incipient fault diagnosis for dynamic process monitoring. The conventional canonical variate analysis (CVA) fault detection approach is extended to form a new monitoring index based on Hotelli...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-02-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/12/4/726 |
| Summary: | This study puts forward a novel diagnostic approach based on canonical variate residuals (CVR) to implement incipient fault diagnosis for dynamic process monitoring. The conventional canonical variate analysis (CVA) fault detection approach is extended to form a new monitoring index based on Hotelling’s <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>T</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>Q</mi> </mrow> </semantics> </math> </inline-formula> and a CVR-based monitoring index, <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>T</mi> <mi>d</mi> </msub> </mrow> </semantics> </math> </inline-formula>. A CVR-based contribution plot approach is also proposed based on <inline-formula> <math display="inline"> <semantics> <mi>Q</mi> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>T</mi> <mi>d</mi> </msub> </mrow> </semantics> </math> </inline-formula> statistics. Two performance metrics: (1) false alarm rate and (2) missed detection rate are used to assess the effectiveness of the proposed approach. The CVR diagnostic approach was validated on incipient faults in a continuous stirred tank reactor (CSTR) system and an operational centrifugal compressor. |
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| ISSN: | 1996-1073 |