Abstract

This study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the fault-specific frequency band (FSFB) in the first step. Statistical features in time, frequency, and wavelet domains were extracted from the fault-specific frequency band. In the second step, all of the extracted features were combined into a single feature vector called a multi-domain feature pool (MDFP). The multi-domain feature pool results in a larger dimension; furthermore, not all of the features are best for representing the centrifugal pump condition and can affect the condition classification accuracy of the classifier. To obtain discriminant features with low dimensions, this paper introduces a novel informative ratio principal component analysis in the third step. The technique first assesses the feature informativeness towards the fault by calculating the informative ratio between the feature within the class scatteredness and between-class distance. To obtain a discriminant set of features with reduced dimensions, principal component analysis was applied to the features with a high informative ratio. The combination of informative ratio-based feature assessment and principal component analysis forms the novel informative ratio principal component analysis. The new set of discriminant features obtained from the novel technique are then provided to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal pump condition classification. The proposed method outperformed existing state-of-the-art methods in terms of fault classification accuracy.

Highlights

  • The multistage centrifugal pump (MCP) converts electrical energy to mechanical energy for industrial processes [1]

  • To overcome interference macrostructural vibration noise these defect modes are filtered from the raw vibration signal

  • Statistical features in time, frequency, and time–frequency domains were extracted from the fault-specific frequency band

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Summary

Introduction

The multistage centrifugal pump (MCP) converts electrical energy to mechanical energy for industrial processes [1]. A survey conducted on 437 defective MCPs revealed that the industry went through a maintenance downtime of 6128 h because of the lack of intelligent FD, resulting in a cost of USD. Defects in the MCP can be categorized into soft defects and hard defects. Hard defects occur abruptly and cause the MCP to stop unexpectedly. Hard defects are physically identifiable and can be addressed by inexpensive and simple analysis; soft defects are dangerous as they slowly affect the MCP performance. To reduce downtime and cost for MCP maintenance, this paper considers the early fault diagnosis of soft defects because of a MS hole (MSH), MS scratch (MSS), and impeller defect (ID)

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