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Smart approach to maintenance

1st November 2016

Posted By Paul Boughton


Moxa’s DA-820 series is an IEC 61850 native PRP/HSR computer

Mark Liu discusses how to implement a predictive maintenance a strategy for substation computers 

Today, computers are used extensively in the bay and station levels of an IEC 61850 substation to manage and control IEDs such as protection relays, PMUs, merging units, fault recorders and GOOSE/SMV analysers, as well as for environmental monitoring and surveillance.

Any computer-related performance issue or failure has the potential to directly impact the operation of a substation or disrupt the power distribution system. Therefore, the reliability and availability of substation computers is a key factor for the efficient operation of a substation, making it essential that these computers be managed on par with the other critical equipment in the substation.

The three typical approaches to maintaining equipment in a power substation are: reactive maintenance (breakdown or run-to-failure maintenance); preventive maintenance (time-based maintenance); and predictive maintenance (condition-based maintenance).

In the case of reactive maintenance, equipment continues to run until it fails. Repairs or replacements of equipment are only undertaken after a problem occurs. Although some substations use this approach, it is not recommended for critical equipment such as computers.

In the preventive maintenance approach, the maintenance activities are scheduled at predetermined time intervals. Computers benefit immensely from time-based maintenance rather than run-to-failure maintenance. For example, some studies have shown that by adopting a predictive maintenance programme over reactive maintenance, users can save anywhere between 12% and 18% on cost.

However, preventive maintenance has some drawbacks:

* If a computer malfunctions before the predetermined maintenance time, the outcome is similar to run-to-failure maintenance 

* Time-based maintenance sometimes involves performance of needless maintenance activities 

* Time-based maintenance can be labour-intensive.

In the case of predictive maintenance, the maintenance activities are scheduled when warranted by mechanical or operational conditions based on periodic monitoring of the equipment and observing unhealthy trends that occur over time. As a result, damaged equipment is replaced before obvious problems occur. Predictive maintenance can deliver 8% to 12% cost savings over preventive maintenance.

A fully functional predictive maintenance strategy works very well if personnel have adequate knowledge, skills, and time to perform the predictive maintenance work. It is by far the best strategy for critical equipment.

Moxa’s predictive maintenance solution, called Proactive Self-Maintenance, consists of a proactive monitoring utility and a centralised proactive remote alert solution.

Proactive monitoring utility

Moxa Proactive Monitoring is a small-footprint, resource-friendly utility that allows users to track a number of system parameters. Proactive Monitoring utilises the hardware sensors in the Moxa computer’s motherboard to monitor the key parts of the computer.

Users can view the current parameter values for these key parts by simply clicking on the icons corresponding to the parameters in the user interface. User-defined key part indicators (KPIs) are used to monitor the key parts. Visible and/or audio alerts are triggered automatically via relay and SNMP traps when these KPIs go over their preset threshold values, making it extremely convenient for operators to avoid system downtime by setting up predictive maintenance tasks well in advance.

Moxa’s proactive remote alert solution provides a number of benefits, including centralised visible/audible alerts to the control room via Ethernet and combined SNMP traps to detect system errors faster and accurately. No relay output is needed on the computer and there are no cabling constraints.

For more information, visit www.engineerlive.com/process 

Mark Liu is with Moxa.









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