Abstract
This
paper presents a novel wireless vibration-based method for monitoring the degree
of feed filter clogging. In process industry, these filters are applied to
prevent impurities entering the process. During operation, the filters gradually
become clogged, decreasing the feed flow and, in the worst case, preventing it.
The cleaning of the filter should therefore be carried out predictively in order
to avoid equipment damage and unnecessary process downtime. The degree of
clogging is estimated by first calculating the time domain indices from low
frequency accelerometer samples and then taking the median of the processed
values. Nine different statistical quantities are compared based on the
estimation accuracy and criteria for operating in resource-constrained
environments with particular focus on energy efficiency. The initial results
show that the method is able to detect the degree of clogging, and the approach
may be applicable to filter clogging monitoring.
Original language | English |
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Pages (from-to) | 17-26 |
Number of pages | 10 |
Journal | Sensors & Transducers |
Volume | 128 |
Issue number | 5 |
Publication status | Published - 2011 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Filter clogging
- Pipeline vibration
- Predictive maintenance
- Energy efficiency