In this study, the coupled ordinary differential equations for the galloping of the first two modes in iced bundled conductors, including in-plane, out-of-plane, and torsional directions, are derived. Furthermore, through numerical analysis, the critical conditions of this modal galloping are determined in the range of wind speed–sag parameters, and the galloping patterns and variation laws in different parameter spaces are analyzed. The parameter space is then divided into five regions according to the different galloping modes. Under the multimodal coupling mechanism of galloping, the impact of single and two kinds of coupled mode galloping on the spatial nonlinear behavior is explored. The results reveal that the system exhibits an elliptical orbit motion during single mode galloping, while an “8” motion pattern emerges during coupled mode galloping. Moreover, two patterns of “8” motion are displayed under different parameter spaces. This research provides a theoretical foundation for the design of transmission lines.

Purpose: The aim of this study is to achieve automated energy capture and charging for the ADXL355 accelerometer, enhance the vibration energy collection efficiency, and widen the energy trapping frequency band of a system in a working environment for bridge health state detection. Methods: A vibration energy harvester based on a magnetic coupling cantilever beam in an orthogonal direction was proposed. The harvester works by adjusting the angle and magnetic spacing between the two cantilever-beam piezoelectric oscillators, enabling the oscillators to produce large-scale and stable vibrations when excited by an external broadband vibration source. Results: Sinusoidal frequency sweep experiments showed that, under an excitation amplitude of 0.2 g, the proposed broadband vibration energy harvester based on orthogonal magnetic coupling double cantilever beams achieved the best energy harvesting performance when the magnetic angle of the double cantilever beam system was 130°, and the radius was 16 mm. In the frequency range of 5–20 Hz, the system can effectively capture higher effective voltages across all frequency bands, with a total captured voltage value of approximately 15.3 V. Compared with the control group, the system’s energy harvesting capacity under this working condition increases by 770%. Additionally, the effective frequency band of the system was broadened by 3.7 Hz. Conclusions: Unlike previous studies, which often limited the angles of the magnetic fields generated by the magnets at the ends of piezoelectric beams to specific values, this study explores the influence of rotating these magnetic fields to general angles on the working frequency band of the structure. The findings provide a new perspective and theoretical basis for the optimal design of broadband vibration energy harvesters.

In this paper, we establish a mathematical model to describe in-plane galloping of iced transmission line with geometrical and aerodynamical nonlinearities using Hamilton principle. After Galerkin Discretization, we get a two-dimensional ordinary differential equations system, further, a near Hamiltonian system is obtained by rescaling. By calculating the coefficients of the first order Melnikov function or the Abelian integral of the near-Hamiltonian system, the number of limit cycles and their locations are obtained. We demonstrate that this model can have at least 3 limit cycles in some wind velocity. Moreover, some numerical simulations are conducted to verify the theoretical results.

To address the challenge of discontinuous operating bandwidth in energy harvesters subjected to ultra-low-frequency human motion and low-frequency vibration environments, this study proposes a wearable frequency up-conversion piezoelectric–electromagnetic hybrid energy harvester (FUCPEEH). In both ultra-low and low-frequency ranges, bidirectional coupling between the piezoelectric and electromagnetic modules enables efficient harvesting of human motion energy as well as low-frequency ambient vibration energy. A theoretical model is established and validated experimentally, demonstrating good agreement between simulation and measurement. Experimental results show that the harvester operates effectively over a broad 1.6–10 Hz frequency range. At a running speed of 9 km h ⁻¹ , the FUCPEEH delivers an output power of 95.8 mW and a power density of 177.4 μ W cm ⁻³ . By processing the piezoelectric signals generated by the FUCPEEH under ultra-low-frequency excitation using deep learning, accurate motion-state recognition and user identity recognition are achieved, with accuracies of 99.79% and 99.53%, respectively. A series of electrical demonstrations, including driving an LED array and charging commercial wireless earbuds, further verifies its capability to power wearable devices. These results indicate that the proposed FUCPEEH has substantial potential for applications in smart-city infrastructure and green intelligent living, such as health monitoring, and human–machine interaction.