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Research Papers

Health Monitoring of Centrifugal Pumps Using Digital Models

[+] Author and Article Information
Amr A. Abdel Fatah

Department of Mechanical Engineering,
Centre of Excellence in Predictive Maintenance,
The British University in Egypt,
El Sherouk City,
Cairo 11837, Egypt
e-mail: amr.abdelkader@bue.edu.eg

Mohammed A. Hassan

Department of Electrical Engineering,
Fayoum University,
Fayoum 63514, Egypt
e-mail: hassanm@fayoum.edu.eg

Mohamed Lotfy

Department of Aerospace Engineering,
Faculty of Engineering,
Cairo University,
Giza 12613, Egypt
e-mail: lotfytaha@cu.edu.eg

Antoine S. Dimitri

Mechanical Department of Design and Production,
Faculty of Engineering,
Cairo University,
Giza 12613, Egypt
e-mail: adimitri@eng.cu.edu.eg

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received August 28, 2018; final manuscript received March 10, 2019; published online May 2, 2019. Assoc. Editor: Soichi Ibaraki.

J. Dyn. Sys., Meas., Control 141(9), 091014 (May 02, 2019) (8 pages) Paper No: DS-18-1405; doi: 10.1115/1.4043225 History: Received August 28, 2018; Revised March 10, 2019

The area of predictive maintenance (PM) has received growing research interest in the past few years. Diagnostic capabilities of PM technologies have increased due to advances made in sensor technologies, signal processing algorithms, and the rapid development of computational power and data handling algorithms. Conventional PM programs are mostly built around analyzing sensors' data collected from physical systems. Incorporating simulation data collected from digital models replicating the physical system with sensors' data can lead to more optimization for operation and maintenance. This paper demonstrates the role of using digital models in implementing effective condition monitoring on centrifugal pumps. Two digital models are used to study the dynamic performance of a centrifugal pump experiencing cavitation condition. The first model is a three-dimensional fully turbulent computational fluid dynamic (CFD) model. Based on the pressure distribution obtained from the CFD, a novel analytical pressure pulsation model is developed and used to simulate the exciting forces affecting the pump. The second digital model is a pump casing dynamic model which is used to predict the casing vibration response to exciting forces due to faulty operating conditions. Results obtained from the digital models are validated using an experimental test rig of a small centrifugal pump. Using this concept, a pump faulty operation can be simulated to provide complete understanding of the root cause of the fault. Additionally, digital models can be used to simulate different corrective actions that would restore the normal operation of the pump.

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Figures

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Fig. 1

Concept of using digital models for fault detection and correction

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Fig. 2

The geometric model of the six bladed impeller: (a) section A-A, (b) elevation, and (c) solid model

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Fig. 3

The geometric model of the five vanned diffuser: (a) section A-A, (b) elevation, and (c) solid model

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Fig. 4

Discretization mesh of impeller and diffuser

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Fig. 5

Vapor volume fraction contours near vanes leading edges at suction side during cavitation

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Fig. 6

Pressure distribution in different flow zones at normal operating condition

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Fig. 7

Normalized Gaussian function pressure pulsations

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Fig. 8

Normalized cosine function pressure pulsations

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Fig. 10

Casing vibration response to pressure pulsation

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Fig. 11

(a) Experimental test rig and (b) accelerometers locations on the pump

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Fig. 12

Power spectrum of the pump casing radial vibration

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Fig. 13

Power spectrum of the pump casing axial vibration

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