Background noise in acoustic-based non-intrusive condition monitoring of steam traps
Environmental impact from operation of steam and condensate systems can be reduced by an introduction of condition monitoring. Benefits of condition monitoring include reduction of downtime and repair costs, maintenance schedules optimisation, and potential reduction of safety risks. The use of acou...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Science Talks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772569325000374 |
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| Summary: | Environmental impact from operation of steam and condensate systems can be reduced by an introduction of condition monitoring. Benefits of condition monitoring include reduction of downtime and repair costs, maintenance schedules optimisation, and potential reduction of safety risks. The use of acoustic-based monitoring provides an advanced approach which is non-intrusive to steam traps operation. However, acoustic signals in an industrial environment can be affected by background noise from neighboring operating equipment which poses a challenge in a development of condition monitoring methods. Acoustic-based methods are sensitive to noise emitted by condensate pumps, blowdown valves, maintenance works, leaking isolation valves, pressure reducing valves, pressure maintaining valves, etc. This study is aiming to highlight the importance of distinguishing operational regimes of monitored steam traps from various background noise sources. This study includes a review with demonstration of different cases of background noise in steam and condensate systems with outcomes of condition monitoring based on analysis of acoustic signals recorded at various manufacturing facilities. This study showed that background noise emitted by pressure maintaining valves and nearby steam traps reduces accuracy of condition monitoring the most. While short events and periodic noise only affect steam leakage rate estimations. |
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| ISSN: | 2772-5693 |