Development of Air Entrainment Detection Method for Pumps Using Motor Current Signals

ABSTRACT Simple and cost‐effective methods for air entrainment detection are required for the efficient maintenance of pump systems. Recently, motor current signature analysis (MCSA) has been gaining attention for motor fault detection. In this paper, we review the characteristics of motor current signals in an air entrainment state and propose an MCSA technique for air entrainment detection. We observed that the foot around the fundamental harmonic spectrum in the power spectral density of current signals increased with an air entrainment. Based on these results, we propose defining a characteristic value which reflects this feature.

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Publication Details

Journal
Electrical Engineering in Japan
Published
2026-02-28
DOI
https://doi.org/10.1002/eej.70021
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Development of Air Entrainment Detection Method for Pumps Using Motor Current Signals

Tomoyuki Iwawaki, Takeru KOBAYASHI, Makoto Kanemaru, Yasuhiro Kamino et al.
Electrical Engineering in Japan
Machine Fault Diagnosis Techniques
article

Development of Air Entrainment Detection Method for Pumps Using Motor Current Signals

Tomoyuki Iwawaki, Takeru KOBAYASHI, Makoto Kanemaru, Yasuhiro Kamino, Ryotaro Shinozuka
article en

Abstract

ABSTRACT Simple and cost‐effective methods for air entrainment detection are required for the efficient maintenance of pump systems. Recently, motor current signature analysis (MCSA) has been gaining attention for motor fault detection. In this paper, we review the characteristics of motor current signals in an air entrainment state and propose an MCSA technique for air entrainment detection. We observed that the foot around the fundamental harmonic spectrum in the power spectral density of current signals increased with an air entrainment. Based on these results, we propose defining a characteristic value which reflects this feature.

Electrical Engineering in Japan
Mitsubishi Electric (Japan) (JP)
Openalex Percentile: Top 32%
Machine Fault Diagnosis Techniques
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