基于多点应力信息融合的斜拉索锚头性能衰退评估原理与光纤智能监测方法研究

Anchor heads are the most complex and critical load carrying parts of stayed cables, as they are the force connection between cables and large-span structures. During the service term, many unfavorable factors such as cycling load and thermal shocks have a bad effect on anchor head, its performance will degrade inevitably. For this problem, the bonding mechanism between epoxy mortar and steel wires will be analyzed based on the drawing constitutive model, and then, the association between gripping force and internal axial stress distribution of anchor head will be explored. Taking "health degree" as the quantitative index, an evaluation model for anchor head state assessment will be established with information fusion of previous multipoint axial stress. On the basis of previous studies, an optic-fiber monitoring method based on pre-planting FBG strain sensors in anchor head will be proposed. And after a research on the stress transferring mechanism among steel wire, epoxy mortar and sensors, the verification experiments will be carried out. Finally, the performance degradation assessment theory and the health monitoring method will be improved.

锚头作为缆索与大跨度结构的受力连接点，是斜拉索结构最为复杂、最为关键的承力部件，然而在复杂荷载及热冲击循环等因素作用下，锚头不可避免的存在性能衰退的情况。针对此问题，利用拉拔本构模型，研究锚固环氧砂浆对钢丝的握裹作用机理，探索握裹作用力与锚头内部轴向钢丝应力分布之间的关联机制，通过对既往轴向多点应力的融合分析，建立以“健康度”为评价指标的锚头衰退状态评估模型。以此为基础，提出基于锚头预植分布式FBG应变传感器的斜拉索锚头光纤智能监测方法，在进行钢丝、锚固环氧砂浆及传感器间应力传递机理研究的基础上，进行验证性试验，完善并确定锚头性能衰退评估系统理论与监测方法。

锚头作为缆索与大跨度结构的受力连接点，是斜拉索结构最为复杂、最为关键的承力部件，然而在复杂荷载及热冲击循环等因素作用下，锚头不可避免的存在性能衰退的情况。在分析冷铸锚头结构特点的基础上，建立了锚头内钢丝与改性环氧填料微元体静载平衡模型，通过分析钢丝与环氧填料间握裹力 对钢丝应力分布特性的影响，将缆索锚头的失效表征为粘接应力 的奇异变化，提出了通过测量钢丝轴向多点应力间接实现对锚头性能状态无损监测的新方法。针对LMLPES7-211型锚头，利用有限元方法分析了锚头内钢丝的轴向应力分布特性。根据冷铸锚头内非均匀应变特性与恶劣环境要求，提出了毛细管封装的应变均化拉丝塔光栅（DTG）测量方案，建立以“健康度”为评价指标的锚头衰退状态评估模型。进行了缆索锚头性能状态监测模拟试验，分别将2支DTG分布式应变传感器植入1#（性能正常）、2#（性能异常）锚头内，对比钢丝分布式应变数据分析可见，1#锚头内应变衰减趋势较为平滑、与有限元仿真结果较为接近，2#锚头应变衰减趋势平滑性不足、且与有限元结果比较最大误差超过40%。另外，还发现性能衰退会导致近锚固始端区段的粘接应力大幅下降，最大达到-2.55 Mpa，近分丝底板锚固区段的粘接应力大幅增加，增加量达到325.2%。通过设置粘接应力合理偏离阈值，就可实现对锚头结构性能状态的在线监测与预警。