Emerging artificial intelligence methods in structural engineering

3D displacement measurement model for health monitoring of structures using a motion capture system

Internet of Things-enabled smart cities: State-of-the-art and future trends

System identification in structural engineering

The dual effects of the Internet of Things (IoT) : A systematic review of the benefits and risks of IoT adoption by organizations

An intelligent structural damage detection approach based on self-powered wireless sensor data

: Currently, pavement instrumentation for condition monitoring is done on a localized and short-term basis. Existing technology does not allow for continuous long-term monitoring and network level deployment. Long-term monitoring of mechanical loading for pavement structures could reduce maintenance costs, improve longevity, and enhance safety. In this article, on-going research to develop and validate a smart pavement monitoring system is described. The system mainly consists of a novel self-powered wireless sensor based on the integration of piezoelectric transduction with floating-gate injection capable of detecting, storing, and transmitting strain history for long-term monitoring and a novel passive temperature gauge. A technique for estimating full-field strain distributions using measured data from a limited number of implemented sensors is also described. The ultimate purpose is to incorporate the traffic wander effect in the fatigue prediction algorithms. Preliminary results are shown and limitations are discussed.

Toward an Integrated Smart Sensing System and Data Interpretation Techniques for Pavement Fatigue Monitoring

Damage detection using self-powered wireless sensor data: An evolutionary approach

By incorporating sensing capabilities in passive radio-frequency identification (RFID) tagging technology it is possible to extend the coverage of Internet-of-Things (IoT) to monitor the health of different segments of a large civil infrastructure like pavement highway, buildings or a multi-span bridge. The challenge in this regard is to deliver energy to the RFID sensors that are embedded inside the structures in a manner that they can continuously sense for occurrence of any rare structural events. This paper summarizes some of the progress that has been made to-date in the area of self-powered R FID sensor networks within the concept of IoT. The core sensor uses a self-powering method which directly harvests computational and storage energy from slight strain-variations in the structure. The event signatures can then be stored on a non-volatile memory and remotely retrieved at a later period of time. In this “sense now retrieve later” paradigm, self-powering is only used for continuous sensing and data-logging of essential statistics; whereas, data retrieval and reconfiguration is achieved using a low-cost commercial RFID system. Another advantage of using a commercial RFID system for data retrieval is that the related standards and FCC compliance are well established and the technology can be easily integrated with other IoT network infrastructure.

Infrastructural health monitoring using self-powered Internet-of-Things

The objective of this paper is to present an overview of on-going work aimed at the development of a sensing system that can be applied toward the long term monitoring of pavement structures. The paper addresses the different challenges related to the successful development and implementation of the system for pavement application. The novel module consists of a miniaturized battery-less wireless sensor capable of detecting the long-term strain history of the pavement structure. It is based on the integration of piezoelectric transducers with an array of ultra-low power floating gate computational circuits. The paper is split into four sections. First, a summary of the development of the sensor electronics is provided. Then, a description of the development of a reliable packaging system that ensures structure integration of the sensor, reasonable survivability under construction conditions, and longevity in harsh environments, is presented. Also, a damage prediction algorithm to estimate the remaining life of the pavement from the sensor output data is discussed. Finally, the use of a probabilistic based interpolation technique for the estimation of full field strain distributions, using measured data from a limited number of implemented sensors, is investigated in the context of exploring the feasibility of large networks deployment.

Fred Faridazar

Papers

An intelligent structural damage detection approach based on self-powered wireless sensor data

Toward an Integrated Smart Sensing System and Data Interpretation Techniques for Pavement Fatigue Monitoring

Damage detection using self-powered wireless sensor data: An evolutionary approach

Infrastructural health monitoring using self-powered Internet-of-Things

A Self-powered Sensing System for Continuous Fatigue Monitoring of In-service Pavements