The invention relates to the technical field of wind
turbine generator
data analysis, and discloses an offshore wind
turbine generator operation
data analysis and
prediction system. The
system comprises a marine environment
data integration module for collecting data to generate a multi-source time-space synchronization
data set; the multi-
modal feature fusion module is used for extracting cross-
modal correlation features to generate a high-dimensional fusion feature
tensor; the dynamic fault prediction module is used for constructing a two-way gating circulation
network model to predict the degradation probability and the residual life of key components of the equipment; and the self-
adaptive optimization control module is used for constructing a multi-target
dynamic programming model to optimize a fan operation strategy. In addition, the
system is further provided with a feedback correction module for correcting prediction
model parameters, and a virtual sensor module based on a
physical information neural network is used for monitoring
tower stress and diagnosing sensor faults. According to the
system, comprehensive monitoring, accurate fault prediction and
optimal control of the offshore wind
turbine generator are realized, the operation efficiency, reliability and safety of the wind turbine generator are effectively improved, and the operation and maintenance cost is reduced.