Built-In Diagnostics for Structural Health Monitoring: An Active Sensing Technique for Civil Infrastructures Applications

9812574 Chang美国和日本调查人员正在进行联合调查，以开发用于监测民用基础设施完整性的内置诊断技术。在美国方面，这项调查将侧重于开发一种主动传感诊断技术，用于识别结构关键区域的异常情况。在日本方面，采用了一种带有分布式传感器的被动感应技术，用于监测结构的全球反应，并定位可能存在异常的关键区域。这项研究将涉及到系统的硬件和软件的开发。硬件开发包括钢筋混凝土结构智能钢筋的设计和制造。智能钢筋将由复合材料制成，内置传感器和执行器网络。传感器和致动器均选用压电材料。内置的执行器将产生所需的诊断信号，这些信号对特定类型的异常或损坏非常敏感，邻近的传感器将记录信号的传输和反射。然后将该区域引入异常之前和之后的传感器测量值的差异进行处理，以识别异常的存在。将开发软件来解释传感器的测量结果。该软件开发的主要重点将集中在通过内置换能器产生诊断信号、信号处理和信号解释，从而作为诊断技术的大脑。研究完成后，将开发一个内置主动传感系统的原型。将进行适当的实验以验证所建议的技术。* * *

9812574 Chang A joint investigation between U.S. and Japanese investigators is conducted to develop built-in diagnostic techniques for the monitoring of the integrity of civil infrastructures. On the U.S. side, this investigation will focus on the development of an active sensing diagnostic technique for identifying anomalies in critical areas of structures. On the Japanese side, a passive sensing technique with distributed sensors for monitoring the global response of the structures and for locating the critical areas where anomalies might be present. This research will involve the development of both the hardware and software for the system. The hardware development includes the design and fabrication of the smart rebar for steel- reinforced concrete structures. The smart rebar will be made of composite materials with a built-in network of sensors and actuators. Piezoelectric materials will be selected as both sensors and actuators. A built-in actuator would generate desired diagnostic signals which are sensitive to a particular type of anomaly or damage, and the neighboring sensors would record the transmission and reflection of the signals. The difference in sensor measurements taken before and after the introduction of an anomaly in the region will then be processed to identify the presence of the anomaly. The software will be developed to interpret the sensor measurements. The major focus of the development of the software will concentrate on diagnostic signal generation by built-in transducers, signal processing, and signal interpretation, thus serving as the brain of the diagnostic technique. Upon completion of the study, a prototype of a built-in active sensing system will be developed. Appropriate experiments will be conducted for verifying the proposed techniques. ***