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This invention provides an autonomous inspection method and system for unmanned aerial vehicles (UAVs) based on a large language model and simulation verification. It includes: parsing natural language commands into a structured domain-specific language (DSL) description using a large language model; mapping the DSL to executable code for the UAV via a Model Control Protocol (MCP); performing multi-dimensional verification of the code in a digital twin simulation environment, including collision and logic checks; if verification fails, feedback error information triggers automatic correction by the large language model until successful; deploying the verified code to a physical UAV for inspection, and implementing dynamic deviation circuit breaking based on virtual-real-time airflow alignment and MCP feedback replanning. This invention solves the problem of safe conversion from natural language to precise control through a DSL intermediate layer and simulation verification closed loop, constructing a semantic-control two-layer decoupled architecture, achieving full-process automation from high-level commands to safe autonomous flight, and significantly improving the intelligence level and operational safety of the inspection process.