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. 2019 Aug 31;19(17):3781.
doi: 10.3390/s19173781.

An Industrial Digitalization Platform for Condition Monitoring and Predictive Maintenance of Pumping Equipment

Michael Short  1 , John Twiddle  2
Affiliations

An Industrial Digitalization Platform for Condition Monitoring and Predictive Maintenance of Pumping Equipment

Michael Short et al. Sensors (Basel). .

Abstract

This paper is concerned with the implementation and field-testing of an edge device for real-time condition monitoring and fault detection for large-scale rotating equipment in the UK water industry. The edge device implements a local digital twin, processing information from low-cost transducers mounted on the equipment in real-time. Condition monitoring is achieved with sliding-mode observers employed as soft sensors to estimate critical internal pump parameters to help detect equipment weasr before damage occurs. The paper describes the implementation of the edge system on a prototype microcontroller-based embedded platform, which supports the Modbus protocol; IP/GSM communication gateways provide remote connectivity to the network core, allowing further detailed analytics for predictive maintenance to take place. The paper first describes validation testing of the edge device using Hardware-In-The-Loop techniques, followed by trials on large-scale pumping equipment in the field. The paper concludes that the proposed system potentially delivers a flexible and low-cost industrial digitalization platform for condition monitoring and predictive maintenance applications in the water industry.

Keywords: IoT; condition monitoring; edge computing; field testing; industrial digitalization; industry 4.0; predictive maintenance; sliding mode observers; soft sensors.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results

Figures

Figure 1
Figure 1
Basic operation of a sliding mode observer.
Figure 2
Figure 2
Overview of current application area.
Figure 3
Figure 3
Detail of the shaft coupling.
Figure 4
Figure 4
Main hardware elements employed in the system.
Figure 5
Figure 5
Main software elements employed in the system.
Figure 6
Figure 6
Overall communications architecture of the proposed system.
Figure 7
Figure 7
Overview of Hardware-In-The-Loop (HIL) testing of embedded real-time systems.
Figure 8
Figure 8
HIL testing of the prototype edge device on a C167 processor.
Figure 9
Figure 9
Comparative analysis of the Simulink-based and edge device-based observers (baseline case).
Figure 10
Figure 10
Comparative analysis of the Simulink-based and edge device-based (coolant flow fault case).
Figure 11
Figure 11
Comparative analysis of the Simulink-based and edge device-based observers (bearing friction factor fault case).
Figure 12
Figure 12
Arrangement of pumps inside pumping house, showing pump 2 (left), pump 3 (middle), and pump 1 (right). Pipework is housed out of view under the metallic walkway.
Figure 13
Figure 13
I/O Schedule for online testing of the device implementation.
Figure 14
Figure 14
Device implementation in IP67 enclosure (bottom right), interface to local PC (bottom left) and instrumentation/communication interfaces (top right).
Figure 15
Figure 15
Online edge device implementation site trials results data: Pump 3 (fixed speed).
Figure 16
Figure 16
Online edge device implementation site trials results data: Pump 2 (variable speed).
See this image and copyright information in PMC

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