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Preload relaxation, caused by elastic interaction between tightened bolts, is one of the major reasons for non-uniformity of pretension force. But how to accurately assess the residual tension of a bolt is still extremely difficult. This paper considers two types of multiple bolted joint and six kinds of tightening sequence. Based on the deformation compatibility equation and elastic interaction stiffness, the generalized mathematical model for evaluating residual preload of bolts is established. Certain model parameters are obtained through numerical simulation. To analyze the influence of initial tightening torque, spacing between bolt holes, bolt material and gasket material on the elastic interaction stiffness, experimental devices and test procedures are developed. Furtherly, preload relaxation models are validated by tests conducted on six types of multi-bolted joint with the same surface roughness. Results of the proposed mathematical model of pretension force show a good consistency with those of corresponding experiment.

Particle swarm optimization (PSO), as a kind of swarm intelligence algorithm, has the advantages of simple algorithm principle, less programmable parameters and easy programming. Many scholars have applied particle swarm optimization (PSO) to various fields through learning it, and successfully solved linear problems, nonlinear problems, multiobjective optimization and other problems. However, the algorithm also has obvious problems in solving problems, such as slow convergence speed, too early maturity, falling into local optimization in advance, etc., which makes the convergence speed slow, search the optimal value accuracy is not high, and the optimization effect is not ideal. Therefore, many scholars have improved the particle swarm optimization algorithm. Taking into account the improvement ideas proposed by scholars in the early stage and the shortcomings still existing in the improvement, this paper puts forward the idea of improving particle swarm optimization algorithm in the future.

In last few years, with the rapid development of robot technology, human-machine interaction technology has increasingly become the focus of many researchers. The security of human-computer interaction is becoming more and more important. As an important part of human-machine interaction, robot active sensing has also become an important field of human-machine interaction. Aiming at the requirement of active sensing technology in the field of human computer interaction, a low-cost data acquisition system for surface pressure sensing is designed by using STM32 microcontroller and film pressure sensor matrix. The system architecture, acquisition circuit and high-speed communication circuit are discussed detailly in this paper. The experimental results show that the system can collect all sensors' data of the pressure matrix, data acquisition frequency is 50Hz. The real-time display of the host computer is realized, and the network expansion interface is reserved to facilitate the expansion of the system. The linear fitting method is used to correct the sensors, and the perception accuracy of the pressure matrix sensors is improved. The pressure sensing surface can be used to create the perception of the floor, the cushion or desktop perceived perception and so on. It is a useful supplement to the field of active perception in the field of human computer interaction.