AUTHOR=Sun Yufang , Liu Huiqian 
  
TITLE=Design and optimization of wireless sensor system for self-powered crawler crane based on piezoelectric energy harvesting
  
JOURNAL=Frontiers in Mechanical Engineering
  
VOLUME=Volume 11 - 2025
  
YEAR=2026
  
URL=https://www.frontiersin.org/journals/mechanical-engineering/articles/10.3389/fmech.2025.1713677
  
DOI=10.3389/fmech.2025.1713677
  
ISSN=2297-3079
  
ABSTRACT=IntroductionCrawler cranes are widely used in large–scale infrastructure construction, where structural health monitoring is essential to ensure operational safety. Wireless sensor networks have become a mainstream solution for crane monitoring; however, conventional battery–powered systems suffer from frequent replacement, complex wiring, and limited service life, which restrict long–term deployment.MethodsTo address these issues, a piezoelectric energy harvesting electromechanical coupling model tailored to crawler crane operating conditions is developed. Furthermore, a low–power wireless communication protocol incorporating cluster–head data aggregation and dynamic duty–cycle adjustment is introduced, enabling deep collaboration between energy harvesting, energy storage, and wireless sensing modules.ResultsSimulation results show that within the resonance frequency range of 30–35 Hz, the optimized piezoelectric energy harvesting module achieves a peak output power of 8.0 mW at an acceleration of 0.5 g, representing a 47.5% improvement over the unoptimized configuration. Under the same excitation level, the energy storage capacitor voltage increases to 3.0 V within 25 s. Field deployment experiments involving six sensor nodes demonstrate that the proposed joint optimization scheme attains an energy utilization rate of 81.5%, while extending the average node lifetime to 397.4 h, which is 65.6% longer than that of the unoptimized scheme.DiscussionThis study proposes a “structure–circuit–communication” collaborative optimization framework for complex vibration environments of crawler cranes. The proposed approach enables long‐term online monitoring of wireless sensor nodes without batteries and provides a feasible technical pathway for upgrading self-powered Internet of Things systems in large‐scale construction machinery.