High precision and real-time acquisition system for interface stress measurement in bridge bearing.

Since the damage of the bridge structure may cause great disasters, it is necessary to monitor its health status, especially the bridge bearing, the important connecting component of the bridge's upper and lower structures. Nowadays, manual inspection is the main method to get the information of the bridge bearings' work status. However, occasional damage of bridge bearing may not be detected in time, and sometime the installation position of the bearing makes the manual inspection on bridge bearing difficult and even impossible. Therefore, in order to know the work status of the bridge bearings timely, an intelligent remote monitoring system for the bridge bearing is developed. A 32-channel real-time acquisition system is designed by using an AD7768-1 analog-to-digital converter and Xilinx Spartan-6 Field Programmable Gate Array for interface stress continuously acquired in the bridge bearing. To assure the good linearity and low noise performance of the monitoring system, the data acquisition card is meticulously designed to reduce noise from both hardware and software and realize high-precision acquisition. Through the establishment of the monitoring server, the compressive stress data can be displayed synchronously and the overpressure situation can be alarmed in real-time. The experimental results show that the accuracy of the calibrated sensor is within 1.6%, and the detection error of the acquisition board is less than 200 µV. The acquisition system is deemed to have considerable advantages in accuracy and applicability.

Dynamic Behaviour of Bridge Girders with Trapezoidal Profiled Webs Subjected to Moving Loads.

The aim of this study is to find out the degradation of dynamic behaviour of bridge girders with trapezoidal profiled webs when subjected to different vehicle moving loads. Finite element modelling based parametric analysis is demonstrated to be desirable in capturing the dynamic deflection and stress state of critical structural details of girders. The model is validated in the modal analysis through a comparison with theoretical eigenfrequencies. The vibration characteristics are shown to be significantly affected by the corrugation details. The structural service life results of analysed bridge girders are in close agreement with experimental data. It is shown that the dynamic nodal velocity and deflection of analysed bridge girders are greatly affected by the magnitude of the load corresponding to the overload of the vehicle in contrast to the vehicle travel speed. Similar observations can be made for the fatigue life prediction analysis related to the crack initiation when unfavourable effects of the overload vehicle are concerned. Presented analytical results using a fracture mechanics approach could be taken as a good basis for the service life assessment of related bridges with the desired level of performance or functionality.

Fatigue Life Appraisal and Its Corrected Stress Intensity Factor for Repaired Off-CentrallyCracked Aluminum Plates.

This paper presents an experimental study on the fatigue life estimation of off-centrally cracked aluminum plates. Typical theoretical equations for off-central, central and edge cracks were reviewed and compared in terms of their sensitive parameters and applicability. A finite element model has been validated in its capacity in modelling the influences of eccentricity and crack size on the boundary correction coefficients. The Forman equation has been employed along with numerical results for the prediction of fatigue lives. Based on the test data, the fatigue life results of aluminum plates with and without patched laminate repair have been compared with codified fatigue classes. It is demonstrated that the repair at the crack tip close to the plate edge is effective in the fatigue life improvement for off-centrally crackedaluminum plates.

Flexible Dual-Mode Tactile Sensor Derived from Three-Dimensional Porous Carbon Architecture.

Detecting and monitoring varieties of human activities is one of the most essential functions and design purposes of different kinds of wearable sensors. Apart from excellent sensitivity and durability, limited by the materials, most of the sensors reported in the literature are capable of detecting signals only on the basis of a sole mechanism. In this work, a dual-mode flexible sensor derived from a high-temperature-pyrolysized 3D carbon sponge (C-Sponge) was proposed as a peculiar sensor material that is able to detect human activities based on fundamentally different mechanisms, by either the triboelectric effect or the piezoresistive effect. The sensor generated an average open circuit voltage up to ∼2 V and short circuit current up to ∼70 nA when being used as self-powered triboelectric sensor, which was sufficiently sensitive for detecting finger touching and plantar pressure distribution of human feet. On the other hand, by incorporating MWCNT into the 3D structure, the sensor at piezoresistive mode exhibited a sensitivity improvement of nearly 20-fold, from less than 40% to more than 800%, and a durability improvement of more than 22-fold (240 000 cycles) compared with those of original C-Sponge fabricated at 1000 °C (10 800 cycles). All the experimental results indicated that the proposed flexible dual-mode sensor is potentially applicable as wearable sensors for human activity monitoring.

Polyurethane/Cotton/Carbon Nanotubes Core-Spun Yarn as High Reliability Stretchable Strain Sensor for Human Motion Detection.

Smart yarns and textiles are an active field of researches nowadays due to their potential applications in flexible and stretchable electronics, wearable devices, and electronic sensors. Integration of ordinary yarns with conductive fillers renders the composite yarns with new intriguing functions, such as sensation and monitoring of strain and stress. Here we report a low cost scalable fabrication for highly reliable, stretchable, and conductive composite yarn as effective strain sensing material for human motion monitoring. By incorporating highly conductive single-wall carbon nanotubes (SWCNTs) into the elastic cotton/polyurethane (PU) core-spun yarn through a self-designed coating approach, we demonstrated that the yarn is able to detect and monitor the movement of human limbs, such as finger and elbow, and even the wink of eyes. By virtue of the covered structure of the cotton/PU yarn and the reinforcement effect of SWCNTs, the composite yarn can bear up to 300% strain and could be cycled nearly 300,000 times under 40% strain without noticeable breakage. It is promising that this kind of conductive yarn can be integrated into various fabrics and used in future wearable devices and electronic skins.