暨南大学

This work establishes a framework for global asymptotic stability of variable-order fractional systems with short memory under an event-triggered impulsive control strategy. Through the fusion of the short-memory principle with variable-order fractional operators, the proposed approach leverages their inherent dynamic order adjustability. This enables the system to accurately characterize time-varying memory properties and respond effectively to its dynamic evolution. Sufficient criteria are deduced to guarantee global asymptotic stability while explicitly excluding Zeno behavior. Finally, a numerical simulation is provided to verify the theoretical results.

Simplified pitting geometries cannot adequately represent the spatial non-uniformity of real tooth-surface damage or its influence on gear vibration. This study proposes a morphology-resolved dynamic modeling framework for profile-shifted spur gears that links experimentally observed pitting morphology, time-varying mesh stiffness (TVMS), and vibration response. Three-dimensional (3D) pitted surfaces at different damage stages are reconstructed from measured tooth-profile data and surface images and mapped to TVMS using a slicing-based potential-energy method. The resulting stiffness is incorporated into a 13-degree-of-freedom dynamic model that further considers measured speed fluctuations and non-uniform pitting among successive teeth. Healthy-state stiffness is compared with finite-element results, and the simulated vibration responses are validated experimentally. The results show that horizontal translations have the strongest influence among the additional degrees of freedom, while measured speed fluctuations under severe pitting increase the RMS by only 0.81% but the peak amplitude by approximately 12.0%. In the final experimental comparison, the deviations in meshing frequency, RMS amplitude, and time–frequency mean energy are 0.04%, 0.37%, and 0.18%, respectively. However, the experimental and simulated dominant peaks occur at different meshing harmonics, indicating limitations in the predicted spectral-energy distribution. The proposed framework provides a physically interpretable route from measured pitting morphology to gear vibration response.

The separation of multicomponent signals with crossing instantaneous frequency (IF) curves remains a fundamental challenge in time-frequency analysis. Although the synchrosqueezed wavelet-chirplet transform (SWCT) enhances time-frequency readability by introducing a chirprate variable, its effectiveness is constrained by the underlying assumption of local linear chirp. Consequently, this method does not perform well when analyzing signals characterized by strong frequency modulation. This paper extends the SWCT framework by relaxing the linear chirp assumption. We model signal components as having polynomial phase behavior over short intervals and derive compact expressions for high-order IF and chirprate reassignment operators. The proposed high-order synchrosqueezed wavelet-chirplet transform (HSWCT) enables accurate estimation of both IF and chirprate, and supports robust mode retrieval even with intersecting IF curves. Another key contribution is a rigorous mathematical analysis of the approximation errors of arbitrary-order reassignment operators for IF and chirprate estimation. When the chirprate vanishes, HSWCT simplifies to the traditional high-order synchrosqueezed wavelet transform. To the best of our knowledge, no theoretical analysis exists in the literature on the approximation of arbitrary-order SST IF reassignment operators to the IF. As a by-product of this work, our established theorem provides such an analysis, thereby filling a gap in the theoretical framework of high-order SSTs.

Wireless sensor networks (WSNs), as a fundamental component of the Internet of Things, are often exposed to multiple interacting failure mechanisms, including local functional failures of sensors and relays, intentional external attacks causing propagated failures with global effects (PFGE), and relay-induced random isolation effects on dependent sensors. These characteristics pose significant challenges for reliability analysis. Existing studies mainly rely on probabilistic combinatorial approaches that evaluate WSN reliability from a static perspective. For such WSNs, however, a lifetime-based modeling framework that explicitly captures the temporal competition among different failure mechanisms is still lacking. This paper develops a lifetime-based modeling framework for the reliability analysis of relay-assisted WSNs with random isolation effects and PFGE. The system lifetime is characterized as a function of local failure and external attack arrival times, together with random functional dependence states under an arbitrary sensor-level structure. Based on this formulation, explicit reliability expressions are systematically derived in terms of the underlying arrival-time distributions and the dependence probability function. A Monte Carlo simulation algorithm is further provided for large-scale systems. The framework is also specialized to modular WSNs, yielding simplified reliability expressions and computable bounds. Numerical studies on body sensor networks and air quality monitoring systems demonstrate the applicability of the proposed approach and reveal the impacts of functional dependence and propagated failures on system reliability.

Catalytic pyrolysis of lignin into benzene, toluene, and xylene (BTX) provides a promising route for producing renewable aromatic chemicals from industrial biomass residues. However, the rational design of highly efficient zeolite-based catalysts remains challenging due to the complex structure of lignin and the strong dependence of product selectivity on catalyst properties. In this study, Fe-modified HZSM-5 catalysts were prepared using sulfate, nitrate, and chloride precursors to elucidate the role of precursor anions in regulating Fe dispersion, textural properties, acidity, and catalytic performance during lignin pyrolysis. The results showed that Fe incorporation preserved the MFI framework while generating secondary mesoporosity and markedly increasing Lewis acidity, leading to a decrease in the Brønsted/Lewis acid site ratio from 3.07 for parent HZSM-5–0.18–0.83 for the Fe-modified samples. Among the catalysts investigated, Fe0.70-Cl/HZSM-5 exhibited the highest BTX relative abundance at 550 °C (69.9%), compared with Fe0.70-S/HZSM-5 (67.2%), Fe0.70-N/HZSM-5 (56.9%), and parent HZSM-5 (41.7%). At 600 °C, Fe0.70-S/HZSM-5 also showed the highest BTX relative abundance (65.3%) than other catalysts, indicating its superior stability over the temperature range of 550–600 °C. In-situ DRIFTS of guaiacol and lignin revealed the progressive removal of methoxy and hydroxyl groups while preserving the aromatic framework. These findings suggested a sequential reaction pathway in which Lewis-acidic Fe sites promoted the activation and deoxygenation of oxygen-containing functionalities, followed by Brønsted-acid-catalyzed cracking, hydrocarbon-pool reactions, and aromatization within the zeolite channels. This study demonstrated that precursor-anion engineering was a simple and effective strategy for tuning the acidity of metal-modified zeolites toward selective lignin valorization to BTX.