Under the leader-follower structure, based on the intermittent event-triggered mechanism, this paper investigates the finite-time formation system problem for unmanned surface vessel clusters with second-order dynamics. Firstly, by using adaptive neural network techniques, unknown nonlinear items are estimated in the systems model. Secondly, a kind of formation control protocol is proposed based on segmented intermittent event-triggered and adaptive methods to reduce communication energy consumption and accelerate cluster convergence. Then, a sufficient condition for unmanned surface vessel clusters to rapidly form formations in finite-time is obtained using theories such as Lyapunov stabilization and finite time. Finally, simulation examples validate the superiority and effectiveness of the proposed algorithms in the paper.