Contract For Wind Farm Maintenance

Swantech’s SWANview Portable System has been selected for use by wind farm operator, York WindPower on the Big Spring and Westex Wind Farms for predictive maintenance and diagnosis of their wind turbines.

Fort Lauderdale, Florida – October 29, 2002 [] The SWANview Portable system is based upon Swantech’s patented Stress Wave Analysis technology and is used for monitoring the operating health of wind turbine rotors, gearboxes and generators. The farms are adjacent to one another and located between Dallas, El Paso, Del Rio, and Amarillo,Texas. Electric power generated by the farms is purchased under contract by TXU Electric & Gas, and are part of TXU’s Renewable Energy program, called “TU Renew.” Phase I of the farm, Big Spring, generates approximately 117 million kWh of electric energy, enough to power 7300 homes. Electric power generation is provided by 46 wind turbines, some of which are the largest wind turbines in the Western Hemisphere standing 371 feet tall with rotor blades of 216 feet in diameter. Phase II, Westex, includes an additional four wind turbines generating an additional 19.5 million kWh of electric energy, enough to power 1300 homes. Both serve residents of Waco, Texas. According to Junior Yanez, Operations and Maintenance Manager, the SWANview Portable system was selected as a predictive maintenance tool for monitoring the condition of wind turbines because it enables technicians to focus repair activities resulting in substantial cost savings. “By using SWAN technology, we are able to monitor all turbines on the farm and determine which are beginning to experience problems. This allows us to address these problems well before catastrophic failure or secondary damage to the machinery occurs,” said Yanez. “We can also isolate the source of damage to the component level and predict remaining useful life. This provides greater control over the maintenance process by allowing us to determine where and when to schedule repair.” SWAN technology is based upon ultrasonic sound waves, which are detected and measured in terms of energy content and then analyzed to identify and trend the incidence of damage in a machine. The software analysis tools also pinpoint the source of damage and provide early warning in terms of the progression of damage. This information is used to schedule maintenance before severe damage to the machine, or equipment failure occurs.
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