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<p>The loading manipulator is a critical component in modern artillery automatic loading systems. Evaluating the reliability of its positioning accuracy is crucial. We initially construct a parametric dynamic model of the manipulator, integrating the control module. Through co-simulation, we discern the relationship between input variables and positioning angle, using a feed-forward neural network to create a surrogate model. We establish a function for manipulator positioning accuracy and use the truncated importance sampling method (JDIS) to determine failure probability and local sensitivity indicators. This study considers the impact of random uncertainties like the friction coefficient, mass error, and contact parameters on positioning accuracy. The examination reveals a manipulator structure reliability exceeding 0.99, meeting engineering requirements. Significant influences include the gear rotation contact process friction coefficient and the manipulator rotation chassis quality sensitivity indicators. Our findings provide an optimization reference based on reliability.</p>

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Research on the reliability and sensitivity of positioning accuracy of loading manipulator based on co-simulation

  • 期刊论文

  • 发表日期：

    2025年1月30日

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  • Guangsong Chen,
  • Yongji Liu,
  • Linfang Qian

摘要

The loading manipulator is a critical component in modern artillery automatic loading systems. Evaluating the reliability of its positioning accuracy is crucial. We initially construct a parametric dynamic model of the manipulator, integrating the control module. Through co-simulation, we discern the relationship between input variables and positioning angle, using a feed-forward neural network to create a surrogate model. We establish a function for manipulator positioning accuracy and use the truncated importance sampling method (JDIS) to determine failure probability and local sensitivity indicators. This study considers the impact of random uncertainties like the friction coefficient, mass error, and contact parameters on positioning accuracy. The examination reveals a manipulator structure reliability exceeding 0.99, meeting engineering requirements. Significant influences include the gear rotation contact process friction coefficient and the manipulator rotation chassis quality sensitivity indicators. Our findings provide an optimization reference based on reliability.