AbstractCables are important components of long-span space structures, cable-supported bridges, slopes, and so on. However, they often suffer from damage such as wire breakage, corrosion, and anchor head loosening, which threatens structural safety seriously. Therefore, it is very important to diagnose and localize their damage. To address this problem, a real-time damage self-diagnosis and self-localization smart cable is proposed. It is made of a polyethylene cover pipe and some parallel intelligent steel strands with the Brillouin distributed monitoring capability. Fiber-reinforced polymer (FRP) and optical fiber are put together in the thermosetting molding process to form the intelligent central wire of each intelligent steel strand. When the side wire of the steel strand reaches the ultimate load, the intelligent central wire only reaches about 50% of its ultimate load, so it can be used in the real-time monitoring of side wires. Numerical models of seven-wire steel strands with different lengths were established, and the broken wire damage was simulated by changing coupling conditions in single and multiple damage cases. To further verify the proposed smart cable, experiments were carried out based on two intelligent steel strands with the length of 34.5 m. Experimental damage cases were simulated by cutting side wires at different positions under different loads. Both numerical and experimental results show that the change in the tension strain of the intelligent central wire can indicate the damaged location of the broken side wire. For a healthy steel strand, the tension strain of the central wire is a constant value; for a damaged steel strand, damage can be localized according to the strain waveform of the intelligent central wire and its ratio of peak strain to stable strain. The proposed smart cable has functions of real-time stress self-sensing, damage self-diagnosis, damage self-localization, damage self-warning of any side wire, and its central wire has excellent corrosion resistance; it can be well used in life-cycle real-time structural health monitoring of cable structures/substructures, which dramatically reduces the probability of cable accidents, and lays a good foundation for smart civil structures.