Fiber Bragg grating (FBG) acoustic emission (AE) sensors have been used in many applications. In this paper, based on an FBG AE sensor, the sensing principle of the interaction between the AE wave and the sensor is introduced. Then, the directionality of the FBG AE sensor on the surface of a thin polymer-bonded explosive (PBX) material is studied. Finally, the time coefficient location method is proposed to correct the AE time detected by the FBG AE sensor, thereby improving the accuracy of location experiments.

Elastic-wave-based structural health monitoring technology has a broad application potential for its sensitivity and ability to achieve regional monitoring. For structures with large damping and specific shapes, the traditional damage monitoring method is limited by the sensor arrangement area and affected by low signal-to-noise ratios, so it is difficult to accurately locate the damage in a structure. To solve this problem, this paper proposed a damage monitoring method based on a sector piezoelectric sensor array for multiple signal classification algorithm. By arranging two sector piezoelectric sensor arrays that are suitable for a specific structure, the damage scattering array signal under the multi-excitation source was obtained and synthesized, the signal-to-noise ratios were improved, and the damage location accuracy was thus improved. The effectiveness of the method was verified by monitoring the damage in a circular bonded structure with a metal ring. Compared with the damage localization methods based on the traditional single excitation source multiple signal classification algorithm, path imaging and delay-sum imaging, this method can achieve better damage location and has a higher localization accuracy.

The solidification sequence during the solidification of fusion-cast explosives is an important parameter for the optimization of the manufacturing process, which can be analyzed by using numerical simulation experiments. However, the numerical simulations are not totally reliable due to the inherent errors in the algorithms and parameters. To address this issue, a measurement method is proposed to monitor the solidification process based on the embedded method of distributed fiber optic sensing. And a method is developed to identify the solid–liquid phase change interface region, which can be effectively demodulated and analyzed for sensing data. The experimental results were verified by using numerical simulations based on casting simulation software and compared. It can be found that the total solidification time and pattern of both are relatively consistent. However, some of the solidification characteristics in the numerical simulation are lack of precision due to the inaccuracy of the heat transfer parameters.

To ensure ammunition safety, a protective structure and pressure detection system are essential; however, there is a lack of an accurate constitutive model to describe the mechanical response characteristics of protective structures composed of various polymer materials. In this work, a constitutive model for the composite structure based on the superposition principle is successfully constructed derived from the quasi-static compression behavior of rigid polyurethane foam (RPUF), silicone rubber foam (SRF), and flexible pressure sensors (FPSs) through experimental investigations. The constitutive model accurately reflects the influence of each type of polymer foam on the mechanical performance of composite structures, underscoring the significance of thickness ratios. Test results within the temperature range of 25 °C to 55 °C validate the model’s accuracy, with an average fitting error of 8.6%. Furthermore, a multi-channel pressure detection system has been integrated into the composite structure. Under conditions of out-of-plane loads ranging from 0 to 10 kilonewtons, the accuracy of the pressure monitoring system, adjusted using the constructed model, has improved by 16%. The constitutive model and the pressure sensing system effectively predict the mechanical properties of the protective structure and enable real-time force state monitoring, which is crucial for ammunition safety and has broader applications for safeguarding other objects.

Self-sensing structures require methods that convert internally measured strain into deformation with explicit mechanical meaning. This study presents a mechanics-based method for reconstructing two one-dimensional responses in 3D-printed polymer specimens containing embedded optical fibres: axial elongation under quasi-static tension and single-plane beam deflection under three-point bending. Baseline-subtracted distributed optical fibre sensing (DOFS) strain is integrated over a prescribed tensile gauge; under bending, multilayer strains are fitted through the section to identify curvature and then integrated between fixed physical supports. Coordinate signs, sensing-layer positions and boundary conditions are prescribed independently of digital image correlation (DIC), which is introduced only after reconstruction as an external validation measurement. Tensile reconstruction gave a DOFS–DIC slope of 1.059, R 2 = 0.999 817 and a direct root-mean-square error (RMSE) of 9.045 μ m. In bending, the median sectional-fit R 2 was 0.9949 and the unscaled reconstructed profile followed DIC with a median correlation of 0.9974; the direct RMSE of 0.462 mm and amplitude ratio of 0.582 retained the observed absolute-amplitude underestimation. Downsampling distinguished the minimum testable information supplied by three layers from the additional diagnostic redundancy of five and nine layers. The resulting method combines high-accuracy axial reconstruction, high-spatial-fidelity bending measurement and residual-based multilayer diagnostics in one traceable internal-sensing framework. The present validation covers one resin batch and one-dimensional dominant loading cases, while multidirectional or non-collinear sensing paths provide a testable route towards future three-dimensional reconstruction.