| | JULY 202019and machine learning techniques, and actionable alerts are requisite in achieving efficient maintenance activity by minimizing both false positive and negative indications.SMART Block® sensors and wave iQTM provide a comprehensive solution in achieving such results. How it works For wind turbines, each element of the drive train has a specific purpose in helping the generator rotate in a purely uniform fashion. As any particular element begins to degrade in health, no matter how small, its operating frequency begins to show up in the output signal of the generator, in the form of a slight anomaly to the overall composite signal (i.e., a distortion). Using proven frequency extraction techniques (mathematically based), these sub-frequency elements can be isolated and monitored over time, for changes in severity. Implementing IoT and Big Data technologies, comparisons are made in real-time, against historical norms of large populations of wind turbines, helping to further reduce the chances of false positive or negative indications.Significant benefits over traditional technologiesVibration sensors: mechanical vibration sensors are designed to detect solely mechanical related problems. However, the generator's electrical output signal contains health information for both mechanical and electrical system components, thus many critical component problems (such as rotor bar and wye ring problems) often can go undetected by vibration sensors.Periodic/portable testing: Component signal distortion (within the generator output signal) has dependency on turbine operating conditions (such as rotor speed, load level, etc.). Therefore, repetitive scans (at each varying condition) are required for accurate baselining and ongoing component health assessments, far beyond what is viable with periodic testing.Easy to deployFischer Block, Inc. offers a suite of SMART Block® sensors which detect microscopic anomalies that cannot otherwise be detected through traditional monitoring systems.Just one SMART Block® is all that is needed per turbine to provide high resolution monitoring the generator output signal; a very simple, non-intrusive installation, either up or down tower.Proven ResultsSample of results from actual case studies:· Spectral energy observed at increasing multiples of generator speed created alert indicating shaft alignment problems · Side-bands on either side of fundamental frequency were detected, revealing rotor bar wye-ring degradation· Excessive energy at Main Bearing Race Frequency detected, exposing a pre-fault condition.· Pad mount transformer detected in saturation, creating a sixth harmonic pulsating torque, detrimental to drive train life, preventing potential catastrophic failure With our patented IoT SMART Block® device and wave iQTM predictive analytics engine, we are helping our customers achieve new levels in wind turbine availability, helping to avoid costly failures and extend the life of these critical assets
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