Condition monitoring of a process filter applying wireless vibration analysis

Pekka Koskela (Corresponding Author), Marko Paavola (Corresponding Author), Jukka Karjanlahti, Kauko Leiviskä

Research output: Contribution to journal › Article › Scientific › peer-review

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 languageEnglish
Pages (from-to)17-26
Number of pages10
JournalSensors & Transducers
Volume128
Issue number5
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed

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Condition monitoring
Vibration analysis
Monitoring
Accelerometers
Vibrations (mechanical)
Energy efficiency
Cleaning
Impurities
Industry

Keywords

  • Filter clogging
  • Pipeline vibration
  • Predictive maintenance
  • Energy efficiency

Cite this

Koskela, P., Paavola, M., Karjanlahti, J., & Leiviskä, K. (2011). Condition monitoring of a process filter applying wireless vibration analysis. Sensors & Transducers, 128(5), 17-26.
Koskela, Pekka ; Paavola, Marko ; Karjanlahti, Jukka ; Leiviskä, Kauko. / Condition monitoring of a process filter applying wireless vibration analysis. In: Sensors & Transducers. 2011 ; Vol. 128, No. 5. pp. 17-26.
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title = "Condition monitoring of a process filter applying wireless vibration analysis",
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.",
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Koskela, P, Paavola, M, Karjanlahti, J & Leiviskä, K 2011, 'Condition monitoring of a process filter applying wireless vibration analysis', Sensors & Transducers, vol. 128, no. 5, pp. 17-26.

Condition monitoring of a process filter applying wireless vibration analysis. / Koskela, Pekka (Corresponding Author); Paavola, Marko (Corresponding Author); Karjanlahti, Jukka; Leiviskä, Kauko.

In: Sensors & Transducers, Vol. 128, No. 5, 2011, p. 17-26.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Condition monitoring of a process filter applying wireless vibration analysis

AU - Koskela, Pekka

AU - Paavola, Marko

AU - Karjanlahti, Jukka

AU - Leiviskä, Kauko

N1 - Project code: 6095

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - Filter clogging

KW - Pipeline vibration

KW - Predictive maintenance

KW - Energy efficiency

M3 - Article

VL - 128

SP - 17

EP - 26

JO - Sensors & Transducers

JF - Sensors & Transducers

SN - 2306-8515

IS - 5

ER -

Koskela P, Paavola M, Karjanlahti J, Leiviskä K. Condition monitoring of a process filter applying wireless vibration analysis. Sensors & Transducers. 2011;128(5):17-26.

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