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Condition Monitoring Of Wind Turbine Blades Using Active And Passive Thermograph

CONDITION MONITORING OF WIND TURBINE BLADES USING ACTIVE AND PASSIVE THERMOGRAPH

  • Project Code :
  • TEMBRE19_70
  • .
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CONDITION MONITORING OF WIND TURBINE BLADES USING ACTIVE AND PASSIVE THERMOGRAPH

The failure of wind turbine blades is a major concern in the wind power industry due

to the resulting high cost. It is, therefore, crucial to develop methods to monitor the integrity of

wind turbine blades. Different methods are available to detect subsurface damage but most require close proximity between the sensor and the blade. Thermography, as a non-contact method, may avoid this problem. Both passive and active pulsed and step heating and cooling thermography techniques were investigated for different purposes. A section of a severely damaged blade and a small “plate” cut from the undamaged laminate section of the blade with holes of varying diameter and depth drilled from the rear to provide “known” defects were monitored. The raw thermal images captured by both active and passive thermography demonstrated that image processing was required to improve the quality of the thermal data. Different image processing algorithms were used to increase the thermal contrasts of subsurface defects in thermal images obtained by active thermography. A method called “Step Phase and Amplitude Thermography”, which applies a transform-based algorithm to step heating and cooling data was used. This method was also applied, for the first time, to the passive thermography results. The outcomes of the image processing on both active and passive thermography indicated that the techniques employed could considerably increase the quality of the images and the visibility of internal defects. The signal-to-noise ratio of raw and processed images was calculated to quantitatively show that image processing methods considerably improve the ratios.

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Package Features

  • RASPBERRY PI
  • IP CAM
  • LCD

Includes

  • RASPBIAN
  • NOOBS
  • MAT LAB
  • PYTHON

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