Bispectrum analysis of motor current signals for fault diagnosis of reciprocating compressors

Abdelhamid Naid, Fengshou Gu, Yimin Shao, Salem Al-Arbi, Andrew Ball

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Abstract: The induction motor is the most common driver in industry and has been previously proposed as a means of inferring the condition of an entire equipment train, predominantly through the measurement and processing of power supply parameters. This has obvious advantages in terms of being non-intrusive or remote, less costly to apply and improved safety. This paper describes the use of the induction motor current to identify and quantify a number of common faults seeded on a two-stage reciprocating compressor. An analysis of the compressor working cycle leads to current signal the components that are sensitive to the common faults seeded to compressor system, and second- and third-order signal processing tools are used to analyse the current signals. It is shown that the developed diagnostic features: the bispectral peak value from the amplitude modulation bispectrum and the kurtosis from the current gives rise to reliable fault classification results. The low feature values can differentiate the belt looseness from other fault cases and valve leakage and inter-cooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis stator current data for the diagnosis of motor drive faults.

LanguageEnglish
Pages505-511
Number of pages7
JournalKey Engineering Materials
Volume413-414
DOIs
Publication statusPublished - Jun 2009
Event8th International Conference on Damage Assessment of Structures - Beijing, China
Duration: 3 Aug 20095 Aug 2009
Conference number: 8

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Reciprocating compressors
Induction motors
Failure analysis
Compressors
Amplitude modulation
Stators
Signal processing
Classifiers
Processing
Industry

Cite this

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title = "Bispectrum analysis of motor current signals for fault diagnosis of reciprocating compressors",
abstract = "Abstract: The induction motor is the most common driver in industry and has been previously proposed as a means of inferring the condition of an entire equipment train, predominantly through the measurement and processing of power supply parameters. This has obvious advantages in terms of being non-intrusive or remote, less costly to apply and improved safety. This paper describes the use of the induction motor current to identify and quantify a number of common faults seeded on a two-stage reciprocating compressor. An analysis of the compressor working cycle leads to current signal the components that are sensitive to the common faults seeded to compressor system, and second- and third-order signal processing tools are used to analyse the current signals. It is shown that the developed diagnostic features: the bispectral peak value from the amplitude modulation bispectrum and the kurtosis from the current gives rise to reliable fault classification results. The low feature values can differentiate the belt looseness from other fault cases and valve leakage and inter-cooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis stator current data for the diagnosis of motor drive faults.",
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Bispectrum analysis of motor current signals for fault diagnosis of reciprocating compressors. / Naid, Abdelhamid; Gu, Fengshou; Shao, Yimin; Al-Arbi, Salem; Ball, Andrew.

In: Key Engineering Materials, Vol. 413-414, 06.2009, p. 505-511.

Research output: Contribution to journalArticle

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AU - Gu, Fengshou

AU - Shao, Yimin

AU - Al-Arbi, Salem

AU - Ball, Andrew

PY - 2009/6

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AB - Abstract: The induction motor is the most common driver in industry and has been previously proposed as a means of inferring the condition of an entire equipment train, predominantly through the measurement and processing of power supply parameters. This has obvious advantages in terms of being non-intrusive or remote, less costly to apply and improved safety. This paper describes the use of the induction motor current to identify and quantify a number of common faults seeded on a two-stage reciprocating compressor. An analysis of the compressor working cycle leads to current signal the components that are sensitive to the common faults seeded to compressor system, and second- and third-order signal processing tools are used to analyse the current signals. It is shown that the developed diagnostic features: the bispectral peak value from the amplitude modulation bispectrum and the kurtosis from the current gives rise to reliable fault classification results. The low feature values can differentiate the belt looseness from other fault cases and valve leakage and inter-cooler leakage can be separated easily using two linear classifiers. This work provides a novel approach to the analysis stator current data for the diagnosis of motor drive faults.

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