The CSU Electromagnetic Microgravity Tower under construction is a new type of drop tower which uses the linear motor to drive the experimental cabin and uses the upthrow and drop method to generate the microgravity environment. The tiny deformation on the supporting structure is the key factor to determine whether the experimental cabin can run smoothly on the track. In order to arrange the strain sensors more scientifically and effectively to monitor it, the improved quantum particle swarm optimization algorithm is applied to the sensor placement optimization. The finite element model is taken as an example to compare and verify the validity and superiority of the three placement optimization strategies of particle swarm optimization algorithm, quantum particle swarm optimization algorithm and improved quantum particle swarm optimization algorithm in the deformation reconstruction. The average absolute error of the improved quantum particle swarm optimization algorithm is only 1. 2% of the maximum deformation. The result shows that the improved method of quantum particle swarm optimization algorithm is effective, and it also confirms that the stochastic algorithm is feasible to optimize the sensor placement for deformation reconstruction.