On January 10, 2025, a fire broke out in the generator of a Siemens Gamesa wind turbine at the 20MW Mel Wind Farm in Rio Grande do Norte, Brazil. Two workers who were carrying out maintenance at the time were rescued by helicopter after they took refuge on top of the turbine’s nacelle. The fire caused an estimated $100,000 in damage, and the workers were taken to a hospital for examination but were later released. The cause of the fire is still under investigation.


플랑크 비전 시스템: 멜 풍력 발전소의 지멘스 가메사 풍력 터빈 화재로 근로자 2명 구조, $100,000 피해 예상

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On January 10, 2025, a fire erupted in the generator of a Siemens Gamesa wind turbine at the Mel Wind Farm in Rio Grande do Norte, Brazil. The wind farm, which has a total capacity of 20MW, is owned by Iberdrola and operated by its subsidiary Neoenergia. At the time of the incident, two workers were performing maintenance on the turbine when the fire broke out. The workers immediately took shelter at a safe area on top of the nacelle, as the turbine’s elevators were not activated due to safety concerns.

Given the emergency situation, Neoenergia swiftly initiated its emergency plan, deploying a helicopter to airlift the workers to safety. Video footage of the rescue operation showed the workers being hoisted by airlift cables before being transported to the ground. Fortunately, both workers were unharmed and were taken to a local hospital for a medical examination. They were later released and are reported to be in good health.

The fire, which caused an estimated $100,000 in damage to the turbine’s generator, is still under investigation. Neoenergia is awaiting the completion of a report that will determine the cause of the fire. This incident highlights the risks associated with wind turbine operations and the critical importance of having robust emergency response plans in place.

In the context of preventing such incidents, early fire detection plays a vital role. With Planck Vision Systems’ advanced thermal imaging technology, wind turbine operators can benefit from continuous monitoring that can detect abnormal temperature changes before they escalate into a full-fledged fire. By integrating such systems, the risk of damage to expensive turbine components can be minimized, and worker safety can be further enhanced.


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