## 1 Introduction
To distinguish the cracking mechanisms, the features of two representative acoustic signals, i.e., matrix cracking and debonding of the interface, were captured and used for the calibration of the AE activities. Further AE post-processing analysis was performed with temporal and spectral descriptors to reveal the damage and healing occurring in the host matrices. The average frequency versus rising time/amplitude index confirmed that the cracking modes contribute to the characteristic spectrum. The principle of micro-X-ray computed tomography is based on the 3D computed reconstruction of a sample from 2D projections acquired at different angles around its axis of rotation. The beam intensity is attenuated after absorption by the different phases and components of the material. The component with higher density absorbs more X-ray energy [9]. In [10], \(\mu\)CT was used to determine the damage volume in quasi-isotropic carbon-fiber-reinforced plastic (CFRP) laminates subjected to low-velocity impacts. It was shown that a damage volume increased from 50 to 150 mm\({}^{3}\) for impact events rising from 3 to 5 J. The laminates incorporated a layer of hollow glass fibers (HGFs) at either the 3 rd or 13 th interface to deliver a self-healing agent. It was shown that the direct interaction between the delamination damage and the HGF is limited. The investigation confirmed that if the delaminations do not cause extensive rupture of the HGF at these interfaces then the healing agent is not released and restoration of mechanical properties cannot be achieved. Nevertheless, the results showed that \(\mu\)CT has great potential in self-healing efficiency estimation. [PERSON] et al. [11] demonstrated a high potential of \(\mu\)CT for observation of local healing events in the fiber-reinforced polymer composites using healing-agent-filled compartmented fibers. Digital image correlation is an optical method that employs tracking and image registration techniques for accurate 2D and 3D measurements of changes in images. This method is often used to measure full-field displacement and strains. AE analysis coupled with DIC was successfully applied by [PERSON] et al. [12] for precise detection of brittle failure under a developing crack movement. The brittle failure occurring due to excessive strain on the polymer bridging the healed crack generated acoustic emissions with an energy level of at least one order of magnitude higher than the background noise and a high rate of occurrence of acoustic events. DIC tests performed in parallel allowed very accurate monitoring of crack creation and widening, also detecting a high rate of increase in the crack opening during failure. In summary, DIC enables overall monitoring of the complete healed area. Chemical and structural changes during crosslinking, such as the formation of linking functional structures in polymers, can be analyzed by Raman micro-spectroscopy. A Raman map reflects the spatial intensity distribution of a selected Raman band. The spatial distribution of vibrational frequencies characteristic of the mobile phase and newly formed crosslinked structures can be visualized in contrast to the bulk material to monitor the healing process. The method is capable of revealing the chemical composition of a sample with sufficient spatial and temporal resolution without disturbing the healing process [13]. [PERSON] et al. [14] applied in situ confocal Raman microscopy for observation of the impact-fractured surface of a self-healing laminate under 15 J impact. They provided a graph showing the curing reaction of the released healing agent in an authentic specimen. Optical microscopy images are usually used as a complementary tool for inspection of healing effect rather than quantification of healing efficiency. For example, in [15], the fractured sample micrographs showed the filling of the self-healing agent in the cracks that resulted in the self-healing of samples. Lamb-wave-based methods in the evaluation of self-healing efficiency have not been reported so far.