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Intelligent bolt-jointed system integrating piezoelectric sensors with shape memory alloys

机译:集成压电传感器和形状记忆合金的智能螺栓连接系统

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This paper describes a smart structural system, which uses smart materials for real-time monitoring and active control of bolted joints in steel structures. The goal of this research is to reduce the possibility of failure and the cost of maintenance of steel structures such as bridges, electricity pylons, steel lattice towers and so on. The concept of the smart structural system combines impedance based health monitoring techniques with a shape memory alloy (SMA) washer to restore the tension of the loosened bolt. The impedance-based structural health monitoring (SHM) techniques were used to detect loosened bolts in bolted-joints. By comparing electrical impedance signatures measured from a potentially damage structure with baseline data obtained from the pristine structure, the bolt loosening damage could be detected. An outlier analysis, using generalized extreme value (GEV) distribution, providing optimal decision boundaries, has been carried out for more systematic damage detection. Once the loosening damage was detected in the bolted joint, the external heater, which was bonded to the SMA washer, actuated the washer. Then, the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. Additionally, temperature variation due to the heater was compensated by applying the effective frequency shift (EFS) algorithm to improve the performance of the diagnostic results. An experimental study was conducted by integrating the piezoelectric material based structural health monitoring and the SMA-based active control function on a bolted joint, after which the performance of the smart 'self-monitoring and self-healing bolted joint system' was demonstrated.
机译:本文介绍了一种智能结构系统,该系统使用智能材料对钢结构中的螺栓连接进行实时监控和主动控制。这项研究的目的是减少钢结构(如桥梁,电力塔,钢格塔等)的故障可能性和维护成本。智能结构系统的概念将基于阻抗的健康监测技术与形状记忆合金(SMA)垫圈相结合,以恢复松开螺栓的张力。基于阻抗的结构健康监测(SHM)技术用于检测螺栓连接中的螺栓松动。通过比较从潜在损坏结构测得的电阻抗信号特征与从原始结构获得的基线数据,可以检测到螺栓松动损坏。为了更系统地检测损坏,已经进行了使用广义极值(GEV)分布提供最佳决策边界的异常值分析。一旦在螺栓连接中检测到松动损坏,则结合到SMA垫圈的外部加热器就会启动垫圈。然后,加热的SMA垫圈轴向膨胀并调节螺栓张力以恢复损失的扭矩。此外,通过应用有效频移(EFS)算法可以补偿由于加热器引起的温度变化,从而提高诊断结果的性能。通过将基于压电材料的结构健康监测和基于SMA的主动控制功能集成到螺栓接头上,进行了实验研究,然后展示了智能“自我监控和自愈螺栓接头系统”的性能。

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