A Fuzzy Comprehensive Evaluation Framework Integrating Time–Frequency Features and Combined Weighting for Matching Impact Signals with Multi-Layer Penetration Response Signals

In impact testing, evaluating multiple-impact signals is critical for verifying whether a test setup can reproduce penetration response signals and ensure reliable results. To overcome the limitations of traditional methods, including incomplete indicator coverage, subjective weighting, and poor consistency, this study proposes a fuzzy comprehensive evaluation (FCE) framework based on time–frequency features and combined weighting. Using multi-layer penetration response signals as the matching target, a multidimensional indicator system covering time-domain features, frequency-domain features, and signal quality and stability is established. A combined weighting method integrating AHP, EWM, and CRITIC is then developed, and subjective and objective weights are fused using the geometric mean method. A fuzzy comprehensive evaluation model is used to quantify the matching degrees of multiple sets of multiple-impact signals, and robustness is verified through weight consistency tests and sensitivity analysis. The results show that the evaluated signal sets are rated “Excellent”. Under reasonable weight combinations, the probability of obtaining an “Excellent” result reaches 99.94%, and the maximum variation caused by a ±10% perturbation in a single indicator weight is only 0.0087. The proposed framework provides a practical tool for evaluating multi-layer penetration response simulations and can be extended to other complex dynamic signal-matching problems.