Aiming at the problem of complex failure mechanism and scarcity of fault samples in coal mining machine height adjustment system, this paper proposes and constructs an experimental platform for coal mining machine height adjustment system based on virtual-real linkage, aiming at realizing the effective acquisition of systematic multi-source fault characteristic data.The experimental platform utilizes multi-domain coupled modeling technology to realize high-fidelity mapping of the physical system, and optimizes the design of mechanical structure and sensing layout through spatial adaptation to ensure the safe operation of the physical entity. Relying on the cooperative operation mechanism of hardware and software subsystems, the platform realizes the dynamic coupling between physical entities and virtual simulation models. Based on the platform, typical fault simulation experiments and extreme working condition simulation experiments are carried out, and the consistency of virtual and real fault data is evaluated by the cosine similarity. The experimental results show that the similarity between the real data and the simulated data are all above 0.9, which fully verifies that the platform has good robustness and can generate accurate and effective fault data. At the same time, the platform can generate key fault characterization parameters that are difficult to be directly monitored in the physical entity, which provides reliable multi-dimensional experimental data support and theoretical support for the intelligent fault diagnosis of coal mining machine height adjustment system.