Wind turbines operate under harsh environmental conditions and continuous mechanical stress. Components such as rotor shafts, gearboxes, generators, and tower structures are subject to wear, imbalance, and structural degradation over time. Unplanned failures not only lead to energy production losses, but also result in costly maintenance and reduced turbine reliability.
Wind turbines operate under harsh environmental conditions and continuous mechanical stress. Components such as rotor shafts, gearboxes, generators, and tower structures are subject to wear, imbalance, and structural degradation over time. Unplanned failures not only lead to energy production losses, but also result in costly maintenance and reduced turbine reliability.
• Rotor imbalance
• Shaft bending or cracking
• Torsional vibration
• Loose bearings
• Eccentric rotation
• Gear tooth wear or breakage
• Surface pitting and spalling
• Excessive backlash
• Gear misalignment
• Overload due to torque fluctuation
• Yaw misalignment
• Pitch motor failure
• Brake system malfunction
• Excessive wear on yaw bearings
• Sensor failure or incorrect readings
• Rotor imbalance
• Shaft bending or cracking
• Torsional vibration
• Loose bearings
• Eccentric rotation
• Gear tooth wear or breakage
• Surface pitting and spalling
• Excessive backlash
• Gear misalignment
• Overload due to torque fluctuation
• Yaw misalignment
• Pitch motor failure
• Brake system malfunction
• Excessive wear on yaw bearings
• Sensor failure or incorrect readings
• Loose stator windings
• Rotor imbalance
• Insulation degradation
• Voltage fluctuations
• Frequency instability
• Overheating
• Corrosion from humidity and condensation
• Structural stress due to wind load
• Increased vibration from external conditions
• Inefficiencies in cooling system
Traditional maintenance in wind farms relies on fixed schedules and reactive repairs — often missing early signs of failure. DS-WG integrates Edge AI-powered DS-Track smart sensors with the DS-Insight platform to monitor critical components such as rotor shafts, gearboxes, pitch systems, and generators in real time. By processing vibration, load, and temperature data directly on the sensor, it detects issues like bearing wear, rotor imbalance, or pitch motor failure before they escalate. This ensures continuous energy generation, lowers maintenance costs, and improves overall turbine reliability.
Traditional maintenance in wind farms relies on fixed schedules and reactive repairs — often missing early signs of failure. DS-WG integrates Edge AI-powered DS-Track smart sensors with the DS-Insight platform to monitor critical components such as rotor shafts, gearboxes, pitch systems, and generators in real time. By processing vibration, load, and temperature data directly on the sensor, it detects issues like bearing wear, rotor imbalance, or pitch motor failure before they escalate. This ensures continuous energy generation, lowers maintenance costs, and improves overall turbine reliability.
Delphisonic’s predictive maintenance system integrates Edge AI-powered DS-Track sensors with the DS-Insight analytics platform to continuously monitor wind turbines in real time. Data is processed directly on the sensor, enabling early detection of failures in critical components like the rotor, gearbox, pitch system, and generator. This helps optimize maintenance planning, reduce unplanned downtime, and ensure uninterrupted energy generati
Delphisonic’s predictive maintenance system integrates Edge AI-powered DS-Track sensors with the DS-Insight analytics platform to continuously monitor wind turbines in real time. Data is processed directly on the sensor, enabling early detection of failures in critical components like the rotor, gearbox, pitch system, and generator. This helps optimize maintenance planning, reduce unplanned downtime, and ensure uninterrupted energy generati
Up to 95% failure prevention, through early detection of faults in components like the rotor, pitch system, and gearbox — minimizing unplanned downtime.
Up to 30% reduction in maintenance costs by eliminating unnecessary part replacements through data-driven scheduling.
Continuous energy output, with predictive analytics helping prevent production interruptions due to mechanical issues.
Remote monitoring of elevated turbines, improving accessibility and safety for maintenance teams in hard-to-reach locations.
At Delphisonic, we have been delivering predictive maintenance and industrial monitoring solutions since 2012 — with a strong focus on wind turbines and renewable energy systems.
We combine AI-powered analytics with edge-based smart sensors to detect failures in rotor shafts, gearboxes, and generator systems — ensuring higher energy output, reduced maintenance costs, and improved turbine reliability.
We don’t just monitor wind farms — we engineer them from within, with deep technical know-how and renewable sector insight.
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