Intelligent vibration monitoring for wind plants decreases turbine downtime

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April 8, 2010

 

Sponsor: N-Tron

 

N-TRON Extends Rugged Line of Fully Managed Industrial Ethernet Switches

N-TRON's newest products are designed to meet the rigorous requirements of wind farms, utilities, including power substations, and other industrial process control applications where management features, noise immunity, and support for longer distances are essential.
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Controlling and Monitoring Wind Farm Installations with Redundant Ethernet Communications

N-TRON® specializes in developing and manufacturing products for the wind energy market. N-TRON switches to provide control in each wind turbine and control, monitor and optimize the operation of the wind turbine fields from a central control room.
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N-TRON Fully Managed Industrial Ethernet Starting at $599

Industrial ruggedness, robust management features, and aggressively priced, click the link above to see the N-TRON difference.
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Using DHCP to minimize equipment setup time

Dynamic Host Configuration Protocol (DHCP) is used widely in enterprise network applications to automatically assign Internet Protocol (IP) addresses to equipment connected to these networks. In this white paper N-TRON discusses how to use DHCP to intelligently assign IP addresses in industrial network applications.
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Request N-TRON's Industrial Ethernet Catalog

N-TRON Corp. develops, manufactures, and markets highly reliable industrial network products designed to solve the most demanding communications requirements for mission-critical MIS, data acquisition, and control applications.
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Intelligent vibration monitoring for wind plants decreases turbine downtime

 

An early failure indicator in wind-turbine equipment is a change in its vibration level. On a typical wind turbine, bearing failure and gearbox damage are major causes of turbine downtime. Key to detecting potential failure of wind turbine equipment before it happens is a continuous monitoring of vibration levels of rotors, gearboxes, and generators. Condition-based monitoring (CBM) for wind turbines traditionally includes gathering large amounts of spectrum data, storing the data, and analyzing it off-line. This type was effective for traditional power generation which relied on a few large turbines that required a few measurement points for their kilowatt output. However, adapting traditional CBM systems to today’s larger distributed base of wind turbines with thousands of measurement points diminishes the cost effectiveness and adds additional system and organization complexity.
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