Research Progress on Concrete Crack Monitoring and Self-Healing Technologies

Abstract

This paper provides a systematic overview of recent advances in intelligent monitoring and self-healing technologies for concrete cracks. In terms of monitoring, laser scanning combined with AI-based image recognition enables high-precision crack classification using 3D point clouds and deep learning algorithms. Wireless sensor networks based on the Internet of Things (IoT), integrated with fiber Bragg grating and edge computing, support real-time dynamic monitoring and risk assessment. Phased array ultrasonic technology locates cracks with depths ≥5 mm through beam synthesis and image reconstruction algorithms. On the self-healing front, microbial-induced calcite precipitation (MICP) utilizes alkaliphilic bacteria to produce calcium carbonate crystals, effectively repairing cracks up to 0.52 mm wide. Shape memory alloys (SMAs) close cracks through phase transformation-induced stress, increasing healing efficiency by 40%. Microcapsule-based systems release encapsulated agents that initiate crystallization reactions, enabling the healing of 0.23 mm cracks within 3 days. However, several technical challenges remain: monitoring systems are costly and environmentally limited, and the effectiveness of self-healing technologies significantly decreases with increasing crack width, leading to reduced long-term performance. Future efforts should focus on the integration of intelligent technologies, materials innovation, and sustainable development to address the trade-off between performance and cost. This review aims to provide a theoretical foundation for the construction of intelligent, self-healing concrete systems.