摘要
针对常用的压实质量评价存在未能够实现压实质量的实时评价,且模型的精度与鲁棒性有待提高等问题,建立一种新的压实质量实时评价模型。该模型由提出的基于核方法(kernel method,KM)与自适应混沌细菌觅食算法(adaptive chaotic bacteria foraging algorithm,AC-BFA)的模糊逻辑构建,同时将被碾材料的物理参数、料源特性参数、施工过程碾压参数作为模型的输入参数,其中被碾压材料的物理参数由振动信号分解后得到的基波与一次谐波的振幅表征。工程应用表明,该模型与常用压实质量评价模型相比,不仅在精度上具有一致性与优越性,而且在加噪数据与异常数据测试中显示出更强的鲁棒性,在进一步嵌入到碾压质量实时监控系统后能够实现压实质量的实时评价。
This study develops a real-time compaction quality evaluation model to improve the low accuracy and robustness of the existing compaction quality evaluation models.This real-time model adopts a newly fuzzy logic based on the kernel method(KM)and adaptive chaotic bacteria foraging algorithm(AC-BFA).Its input parameters consist of the physical parameters of compacted material,such as the amplitudes of the first harmonic and fundamental wave decomposed from the vibration signal,the characteristic parameters of material source,and the rolling parameters of construction process.Engineering application shows that compared with the commonly used compaction quality evaluation models,the real-time model is more accurate and superior showing stronger robustness in noise data tests and abnormal data tests,and it can achieve real-time evaluation of compaction quality when embedded into a compaction quality real-time monitoring system.
作者
王佳俊
钟登华
关涛
佟大威
邓韶辉
WANG Jiajun;ZHONG Denghua;GUAN Tao;TONG Dawei;DENG Shaohui(State Key Laboratory of Civil Engineering Simulation and Safety,Tianjin University,Tianjin 300350)
出处
《水力发电学报》
EI
CSCD
北大核心
2019年第3期165-178,共14页
Journal of Hydroelectric Engineering
基金
国家自然科学基金雅砻江联合基金(U1765205)
国家自然科学基金创新群体基金项目(51621092)
国家自然科学基金(51339003)
关键词
压实质量
核方法
自适应混沌细菌觅食算法
模糊逻辑
实时评价
compaction quality
kernel method
adaptive chaotic bacteria foraging algorithm
fuzzy logic
real-time evaluation
