Design and Development of Smart Self-Sensing Composite Materials for Real-Time Structural Health Monitoring Applications

Abstract

The increasing demand for intelligent infrastructure systems and advanced structural safety technologies has accelerated the development of smart materials capable of real-time condition monitoring and self-diagnostic functionality. Conventional structural health monitoring methods often rely on external sensing devices and periodic inspection procedures, which may result in delayed damage detection, increased maintenance costs, and reduced monitoring efficiency. This research presents the design and development of smart self-sensing composite materials for real-time structural health monitoring applications to enhance damage detection capability, structural reliability, and intelligent monitoring performance. The proposed study investigates the integration of conductive nanomaterials, piezoresistive reinforcements, and advanced composite matrices to develop multifunctional composite materials capable of simultaneously carrying structural loads and sensing mechanical deformation. Experimental characterization and numerical analysis techniques are employed to evaluate the electromechanical behavior, sensing sensitivity, mechanical strength, and durability performance of the developed self-sensing composites under varying loading conditions. The framework further examines strain response characteristics, crack detection capability, conductivity variation, and damage localization mechanisms during structural loading and cyclic deformation processes. Performance evaluation is conducted using parameters such as sensing accuracy, strain sensitivity, electrical resistance variation, tensile strength, fatigue resistance, response time, and long-term structural stability.