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A Research on Road and Bridge detection Based on Test detection Technology

Journal of World Architecture 2022年第4期6卷 34-43页

作者： Hongwei Guo Yi Zhang China Merchants Chongqing Highway Engineering Testing Center Co. Ltd.Chongqing 400064China China Merchants Chongqing Communications Technology Research&Design Institute Co. Ltd.Chongqing 400067China

The existence of karst cave at the bottom of bored piles has a great impact on projects under construction and the surrounding *** bored piles require slurry wall protection,the current geophysical exploration method cannot effectively detect the karst cave at the bottom of the piles in the *** with the characteristics of stress wave propagation,the sonar detection method is *** sonar detector can realize the transmission and acquisition of on-site sonar *** method makes full use of the mud conditions of bored cast-in-place piles,and the development of karst caves can be tracked and detected within 10 meters at the pile bottom during the drilling *** has several advantages,including low cost,high speed,and high *** paper verifies the application of sonar detection technology in practical engineering through specific engineering *** research results put forward a new solution for cave exploration in karst areas,especially in liquid environment.

关键词： Karst Cave detection sonar detection Application research

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Online AUV Path Replanning Using Quantum-Behaved Particle Swarm Optimization with Selective Differential Evolution

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Computer Modeling in Engineering & Sciences 2020年第10期125卷 33-50页

作者： Hui Sheng Lim Christopher K.H.Chin Shuhong Chai Neil Bose National Centre for Maritime Engineering and Hydrodynamics Australian Maritime CollegeUniversity of TasmaniaLauncestonTAS7250Australia Memorial University of Newfoundland St.John’sNLA1C 5S7Canada

This paper presents an online AUV(autonomous underwater vehicle)path planner that employs path replanning approach and the SDEQPSO(selective differential evolution-hybridized quantum-behaved particle swarm optimization)algorithm to optimize an AUV mission conducted in an unknown,dynamic and cluttered ocean *** proposed path replanner considered the effect of ocean currents in path optimization to generate a Pareto-optimal path that guides the AUV to its target within minimum *** optimization was based on the onboard sensor data measured from the environment,which consists of a priori unknown dynamic obstacles and spatiotemporal *** sensor arrangements for the forward-looking sonar and horizontal acoustic Doppler current profiler(H-ADCP)were considered in 2D and 3D *** on the simulation results,the SDEQPSO path replanner was found to be capable of generating a time-optimal path that offered up to 13%reduction in travel time compared to the situation where the vehicle simply followed a path with the shortest *** proposed replanning technique also showed consistently better performance over a reactive path planner in terms of solution quality,stability,and computational *** of the replanner was verified under stochastic process using the Monte Carlo *** generated path fulfilled the vehicle’s safety and physical constraints,while intelligently exploiting ocean currents to improve the vehicle’s efficiency.

关键词： Autonomous underwater vehicle path planning particle swarm optimization sonar detection Monte Carlo methods

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