Turbine
- VIDUR is considered to be a sound indicator of a machine's overall health state.
- Developed condition monitoring strategy can be applied for detecting excessive vibration levels that can lead to engine component failure.
- Vidur continuously monitors the turbine shafts for torsional vibration.
- CATS machine-learning algorithms do not rely on the quality of the training data but rather adaptively classify the different states/operation condition of the engine examined.
Mast Structural health Monitoring
- Structural health of Mast is very important.
- Visual examination limits the determination and distinguishing extent of damage.
- VIDUR can be used to monitor condition and vibration monitoring of Mast.
- Vidur scan the complete Mast esp. inaccessible areas. Our system thereby identifies internal damage that cannot be collected by high resolution image.
Following are the features of damage data collection.
- Level 1 : Detection- simply answers the question: is there a damage?
- Level 2 : Localization- capable of specifying the location of the damage within the structure
- Level 3 : Assessment- capable of specifying the type and extent of damage
- Level 4 : Prediction- capable of estimating the remaining useful life (RUL) and safety
Vidur Recognizing the types of structural defects :-
- Identifies any signs of material deterioration or any signs of structural distress and deformation.
- Identifies any alteration and addition in the structure, misuse which may result in overloading.
- Load testing of flexural members to be carried out In case the core test results do not satisfy the requirements.
- Crack, Damage or overlain with material, Potential / prospective fractures
- Increasing gaps between disjointed hinges, potential impact areas while landing, etc.
- Reducing time interval between Diagnosis and Prognosis.