Graphene as a Piezoresistive Material in Strain Sensing Applications

High accuracy measurement of mechanical strain is critical and broadly practiced in several application areas including structural health monitoring, industrial process control, manufacturing, avionics and the automotive industry, to name a few. Strain sensors, otherwise known as strain gauges, are fueled by various nanomaterials, among which graphene has attracted great interest in recent years, due to its unique electro-mechanical characteristics. Graphene shows not only exceptional physical properties but also has remarkable mechanical properties, such as piezoresistivity, which makes it a perfect candidate for strain sensing applications. In the present review, we provide an in-depth overview of the latest studies focusing on graphene and its strain sensing mechanism along with various applications. We start by providing a description of the fundamental properties, synthesis techniques and characterization methods of graphene, and then build forward to the discussion of numerous types of graphene-based strain sensors with side-by-side tabular comparison in terms of figures-of-merit, including strain range and sensitivity, otherwise referred to as the gauge factor. We demonstrate the material synthesis, device fabrication and integration challenges for researchers to achieve both wide strain range and high sensitivity in graphene-based strain sensors. Last of all, several applications of graphene-based strain sensors for different purposes are described. All in all, the evolutionary process of graphene-based strain sensors in recent years, as well as the upcoming challenges and future directions for emerging studies are highlighted.

Eliminating the Influence of Axle Parameters in Influence Line Identification

Accurate and rapid acquisition of the strain influence line of continuous beam plays a positive role in promoting the wide application of structural health monitoring. The structural response obtained from the sensors is used to estimate the strain influence line. However, most estimation methods ignore the influence of axle parameters on the structural response, resulting in a large error in identifying the strain influence line. This paper presents a method for eliminating the influence of axle parameters of moving vehicles on strain responses to estimate the strain influence line of continuous beams based on the long-gauge strain sensing technology. By analysing the mechanical characteristics of the multi-span continuous beam, a theoretical strain influence line expression is first established to obtain the strain influence line of the continuous beam accurately. The structural response only caused by axle weight, obtained by eliminating the influence of axle parameters, is then estimated for calibrating the theoretical strain influence line. Finally, different lane tests are also considered to solve the influence of different transverse position relations on the proposed method between the monitoring unit and the lane. Finally, numerical simulations are adopted to illustrate the effectiveness of the proposed identification method by simulating the strain time histories induced by a multi-axle vehicle. A field test also demonstrates the validity and feasibility of this method.