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<p>During the rapid startup and braking of the crawler crane’s slewing mechanism, excessive transient pressure peaks in the hydraulic motor’s inlet and return lines generate significant hydraulic shock. This shock induces intense vibration in the cab, compromising operational safety and reducing the equipment’s service life. First, baseline hydraulic data were analyzed to identify the underlying causes of the hydraulic shock. Subsequently, a hydraulic system optimization model was developed, and a co-simulation model of the crawler crane was established using AMESim and Adams to validate the effectiveness of the proposed optimization scheme. Finally, the simulation results were verified against field test data. The results demonstrate that the optimized hydraulic system reduces hydraulic shock by approximately 50% in simulations, with a validated simulation accuracy exceeding 90% based on real machine measurements.</p>

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Research on hydraulic shock suppression of crawler crane slewing mechanism based on hydraulic simulation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月7日

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  • Yulan Wei,
  • Yuncong Gu,
  • Yang Zhang,
  • Tongxi Zhu,
  • Boyang Zhang,
  • Qingzhu Zhang,
  • Qiang Zhang,
  • Bing Li

摘要

During the rapid startup and braking of the crawler crane’s slewing mechanism, excessive transient pressure peaks in the hydraulic motor’s inlet and return lines generate significant hydraulic shock. This shock induces intense vibration in the cab, compromising operational safety and reducing the equipment’s service life. First, baseline hydraulic data were analyzed to identify the underlying causes of the hydraulic shock. Subsequently, a hydraulic system optimization model was developed, and a co-simulation model of the crawler crane was established using AMESim and Adams to validate the effectiveness of the proposed optimization scheme. Finally, the simulation results were verified against field test data. The results demonstrate that the optimized hydraulic system reduces hydraulic shock by approximately 50% in simulations, with a validated simulation accuracy exceeding 90% based on real machine measurements.