Abstract
The effective control of loads acting on shield tunneling machines is vital for the equipment operating security. The identification of shield machine loads is a non-linear multi-factor problem. This article proposes an identification method for shield machine loads by using the Particle Swarm Optimization (PSO) based Support Vector Machine (SVM). A PSO-SVM identification model is developed based on on-site data of a subway project. This model implements multi-parameter input related to loads, which reflects the mapping from loads to geological parameters and operating parameters during tunneling. The comparison between identification results and the on-site data verify the accuracy of the PSO-SVM method. This work can offer helpful references for the loads control.
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