The invention relates to the technical field of TBM equipment, and discloses a pumped storage
power station underground cavity TBM applicability evaluation method, which comprises the following steps: S1, firstly
carding an existing framework of pumped storage
power station underground cavity TBM applicability evaluation, and defining core technical elements and a protection range of the framework; an evaluation framework of non-AHP driving, dynamic multi-
source data fusion and
machine learning enabling is provided. According to the method, an evaluation framework of non-AHP driving, dynamic multi-
source data fusion and
machine learning enabling is provided, an
index system is constructed, the
index system is divided into static indexes (in a
design stage, cavern burial depth, surrounding rock category and
turning radius) and dynamic indexes (in a construction stage, TBM attitude error, cutter wear rate, surrounding rock deformation rate and ventilation efficiency), a real-time
monitoring system is integrated, and the dynamic index is divided into a dynamic index and a dynamic index; and data such as TBM attitude, cutter wear and surrounding rock deformation are input into the model in real time, and the applicability
score is dynamically updated, so that the method has the advantages of high pertinence, comprehensive
index system and the like.