## 1 Introduction  
In recent years, considerable attention has been paid to the health monitoring of advanced composite structures. Damage identification through various non-destructive testing techniques predict or diagnose the health of composite structures [1; 2; 3]. Reactive Powder Concrete (RPC), an emerging materials, are widely concerned in railway engineering, roads, buildings, airports and nuclear industrial facilities--ultra high strength, high toughness and high durability [4; 5; 6; 7; 8; 9]. However, there are few researches on damage identification and detection of composite structures using RPC as raw materials. It is critical to popularize intelligent damage monitoring technology of RPC structure damage. Certain damage, which have considerable impact on structure reliability and security, are inevitably retained because of the influence of fatigue load [10; 11; 12]. The process of causing damage caused by cyclic loading includes the combined results of the cumulative process of crack initiation, expansion and final fracture. When the RPC structure is subjected to a continuous fatigue load, initial microcracks appear on the surface of the structure. The stress generated by the matrix crack increases and continues to aggregate, expanding and eventually forming macroscopic cracks. Scholars evaluate the health status of the structure by monitoring the development of damage [13; 14; 15]. Finding damage in time and predicting injuries is the key to avoiding temporary accidents. Therefore, it is very necessary to fully grasp the development of crack damage as well as find an intelligent method to quickly and conveniently monitor the health of the structure. At present, the research on RPC mainly focuses on the influence of material parameters on its performance and the establishment of constitutive models. However, there is a lack of investigations on the damage characterization of materials and damage evolution mechanism [5; 16; 17]. The stress-strain characteristics of RPC under fatigue loading are nonlinear. Therefore, it is important to use appropriate non-destructive testing methods to probe the quality of RPC structures. Accompanied by the destruction process, the structure is deformed and accompanied by local crack damage, which can be recorded by the 3D laser scanning technology (3D LST). Some scholars have found that 3D laser scanning can be used as an effective technique for fatigue damage accumulation research in RPC (see, for example, [18; 19; 20] as well as [21]). The 3D LST can be used to continuously monitor the development of damage or structure deformation and defects in RPC structure dynamically. In addition, we can use image processing methods to correlate the damage generation process with the feature parameters of the 3D image. The damage mode of RPC is extremely complicated, and the displacement and deformation characteristics exhibited during the fatigue loading process are obvious, which indicates that the 3D LST is an extremely effective technique for detecting the damage process. Moreover, many recent studies show that in the detection method of damage, the 3D LST, which can quickly and accurately implement structural modeling, non-destructive, non-contact, and does not require a light source and cost of wiring, has significant advantages [22; 23]. At the same time, in the intelligent method of pattern recognition, artificial intelligence recognition technology, such as clustering technology and data mining, which can accurately and quickly identify the type of the damage, has received widespread attention. These results open the door to research the life prediction and mechanical behavior of RPC structure. More importantly, the 3D laser scanning technology affords unique advantages in the fatigue damage detection of RPC structure because it can evaluate the information contained in the damage to assess damage on-line. However, the study of bending fatigue damage performance is extremely complicated.