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CASE STUDY: VIBRATION

According to a US Energy Information Association study, operating costs at refineries represent approximately 23% of the gross margin. Maintenance expense is responsible for 24% of those operating costs.

Condition based maintenance programmes have the potential to reduce maintenance costs by 15%.

In the past, purchasing a machine condition monitoring system for essential or general-purpose machinery required a large initial commitment and investment from the customer. Most customers monitor ‘essential’ and ‘general purpose’ equipment with manual data collection programmes and portable instruments.

Over the past 15 to 20 years, however, maintenance and reliability experts have not always been able to meet their objectives using this methodology on machinery that fell into the ‘essential assets’ category.

In order to reach the reliability associated with a continuous scanning system, a large amount of field wiring had to be installed to transmit the signal to the data acquisition computer.

Companies that used a portable data collector on ‘essential’ and ‘general purpose’ assets had a much smaller initial hardware cost, but a much more considerable human resource expense. In order to take readings at scheduled frequencies, plants would need to commit personnel and a significant time commitment.

This commitment became more acute for remote machines or machines installed in hazardous locations or those located in areas that were not readily accessible.

GE Energy’s Bently Nevada Essential Insight.mes system was developed to address these issues.  The facilities where this technology was prototyped, and later proven, are some of the most difficult anywhere, combining extremely challenging environments for radio frequency (RF) communication interference and aggressive chemical and atmospheric conditions. This ability provided customer confidence that the system is robust, reliable, and field-proven.

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The technology has the potential to remotely monitor rotating equipment, where using handheld monitors is dangerous or difficult and has been further tested at ‘Uthmaniyah Gas-Oil Separation Plant-10 (UGOSP-10)’.

In the South Ghawar Producing Department (SGPD), the trial was conducted on the UGOSP’s air-compressor motors to monitor vibration, a key indicator of the equipment’s status. The trial was used to test the wireless sensor technology for its effectiveness in predictive maintenance and its feasibility.

“The trial highlights SGPD’s continuous efforts to capitalise on new technologies to improve plant reliability and optimise operational costs,” said a member of the South Ghawar Engineering Division team.

The Essential Insight.mesh system, while not designed for continuous real-time monitoring, is  suited for use where it would be difficult or dangerous to monitor with handheld data collectors, or where frequent samplings are required. Cost savings are expected over hard-wired systems with similar diagnostic features.

In most instances, the wireless technology can be installed and commissioned with no interruption in plant operations. The wireless sensor network is battery-powered and can be configured to measure vibration or temperature.

The setup at Uthmaniyah GOSP-10 involved five sensors, a wireless network gateway and a laptop.

Magnetically mounted vibration sensors were installed on two air-compressor motors. The remaining sensors were used as repeaters in locations throughout the plant to set up the mesh network architecture and to strengthen the signals. The laptop and wireless network receiver were installed in a room over 75 ms from the air compressors.

The trial equipment operated unattended for four weeks. Engineers concluded that the wireless monitoring technology is a feasible alternative to handheld or hardwired monitoring. The instrument engineer leading the trial commented: “A wireless monitoring system like this is particularly attractive for essential machines, which demand a more frequent monitoring rate than a portable system can deliver.”

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