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On the basis of theory studies, wind turbine reliability growth assessment and prediction method were studied systematically. System reliability synthesis and prediction method of the MW level of wind turbine were discussed during the scheme demonstration and design stage. Wind turbine reliability growth bayes statistical inference was analyzed based on non-information prior and uniform prior information in the field debugging and trial operation stage. In the operation stage, dynamic reliability assessment and prediction method based on AMSAA model were studied using field data, further research on the problems of wind turbine reliability growth prediction was studied with instant and delayed corrective actions. And the reliability growth prediction for the key components reserve number of the wind turbine was discussed for maintenance and management. The above studies play an important role in the wind turbine reliability analysis, operation and maintenance, scientific management and decision-making.
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sun_y_q(½ð±Ò+10, ·­ÒëEPI+1): 2011-06-13 00:07:08
On the basis of theoretical studies, we investigated assessment and prediction method of wind turbine reliability growth.
In the scheme demonstration and design stage, we discussed system reliability synthesis and prediction method of the MW level wind turbine. In the field debugging and trial operation stage, based on Bayes statistical inference with non-information prior and uniform prior information, we predicted wind turbine reliability growth. In the operation stage, based on AMSAA model, we discussed dynamic reliability assessment and prediction of possible fault using field data. Further we studied the problems of wind turbine reliability growth prediction was with instant and delayed corrective actions. We discussed the reliability growth prediction for the key components reserve number of the wind turbine For the maintenance and management. The above studies play an important role in the wind turbine reliability analysis, operation and maintenance, scientific management and decision-making.
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