The Dung Beetle optimization (DBO) algorithm is an innovative and effective metaheuristic algorithm widely recognised for its excellent numerical optimization performance. However, DBO converges slowly and tends to fall into local optima due to the imbalance between exploration and exploitation, the lack of collaborative search capability and population diversity. To overcome these challenges, this paper proposes a dung beetle optimization algorithm based on multi-strategy collaborative enhancement (MDBO). The algorithm constructs a “search-enhance-escape” collaborative optimization framework through adaptive regulation and elite information sharing, and contains three major innovations: (1) a dual adaptive search strategy, which combines the adaptive contraction mechanism of the leader’s centre of mass and the brownian bidirectional crossover perturbation strength regulation, to enhance the population diversity and collaborative search ability of the dung beetle, achieving a dynamic balance between exploration and exploitation; (2) Elite Enhanced Solution Quality (EESQ) mechanism, which improves the quality of both the current local and global optimal positions and accelerates convergence through structured elite information and dual-phase adaptive perturbation; and (3) Dynamic Oppositional Learning (DOL), which introduces an asymmetric adaptive perturbation in the dung beetle’s foraging and Breeding phases and enhances the ability to escape from local optima. The three act synergistically to achieve a more efficient optimised search. The performance of MDBO is evaluated using the IEEE CEC 2017, CEC 2019 and CEC 2020 benchmarking functions. Compared to the DBO algorithm, the MDBO algorithm improves the convergence accuracy and stability on the CEC2017 benchmark functions by 60.91 % and 63.98 %, respectively. For the CEC2019 benchmark functions, the corresponding improvements are 54.47 % and 41.36 %, while for the CEC2020 benchmark functions, they are 50.71 % and 55.16 %, respectively. In addition, its overall performance is evaluated against two complex real-world engineering problems: UAV path planning and wireless sensor network coverage optimization. The experimental results show that MDBO provides very competitive optimization results compared to DBO, two highly referenced algorithms and five advanced algorithms.

The giant magnetoimpedance effect of multilayered thin films under stress has great application prospects in magnetic sensing, but related studies are rarely reported. Therefore, the giant magnetoimpedance effects in multilayered thin film meanders under different stresses were thoroughly investigated. Firstly, multilayered FeNi/Cu/FeNi thin film meanders with the same thickness were manufactured on polyimide (PI) and polyester (PET) substrates by DC magnetron sputtering and MEMS technology. The characterization of meanders was analyzed by SEM, AFM, XRD, and VSM. The results show that multilayered thin film meanders on flexible substrates also have the advantages of good density, high crystallinity, and excellent soft magnetic properties. Then, we observed the giant magnetoimpedance effect under tensile and compressive stresses. The results show that the application of longitudinal compressive stress increases the transverse anisotropy and enhances the GMI effect of multilayered thin film meanders, while the application of longitudinal tensile stress yields the opposite result. The results provide novel solutions for the fabrication of more stable and flexible giant magnetoimpedance sensors, as well as for the development of stress sensors.

A sensitive non-contact sensing system based on the CoFeNiSiB amorphous ribbon giant magnetoimpedance (GMI) effect is proposed for current testing. The sensing system consists of a GMI probe, a sinusoidal current generator, a voltage follower, a preamplifier, a low-pass filter, and a peak detector. Four different GMI probes derived from amorphous ribbon meanders are designed and fabricated through MEMS processes. GMI probes were driven by a 10 MHz, 5 mA AC current. A permanent magnet was used to provide a bias magnetic field for the probe. The effect of the bias magnetic field on the output DC voltage was investigated. This non-contact current sensing system exhibits good sensitivity and linearity at a bias magnetic field H_bias = 15 Oe. The sensitivity can reach up to 24.2 mV/A in the ±1.5 A range.

A new three-axis inertial switch is proposed. The triangle-structured movable electrode is designed to improve the inertial switch’s dynamic response performance, especially the movable electrode’s dynamic stability performance. The static mechanical analysis indicated that the displacement of the movable electrode to the fixed electrode in the sensitive direction is the minimum when the acceleration is applied to this designed inertial switch. The dynamic simulation analysis showed that the threshold of the designed inertial is about 235 g. The threshold in the non-sensitive direction is about 240 g, 270 g, 300 g, and 350 g when the directions of applied acceleration deviate 15°, 30°, 45°, and 60° from the sensitive direction, respectively. These results indicated that the designed inertial could resist the impact in non-sensitive directions and improve the stability in sensitive directions. The prototype of the inertial switch was fabricated and tested successfully. The testing results indicate that the threshold of the fabricated inertial switch is about 219 g. The test results verify the dynamic stability performance of the designed inertial switch.

Co-based amorphous wires (Co-AWs) are functional materials renowned for their high impedance change rate in magnetic fields and a pronounced giant magnetoimpedance (GMI) effect. In this study, magnetron sputtering (MS) and dip-coating (DC) techniques were employed to fabricate carbon-based nanocoatings aimed at modulating the GMI properties of Co-AWs. The magnetic properties and GMI responses of the composite Co-AWs with carbon-based coatings were comparatively analyzed. The results demonstrate that both methods effectively enhanced the GMI properties of the coated Co-AWs. The DC method emerged as a rapid and efficient approach for forming the coated film, achieving a modest enhancement in GMI performance (10% enhancement). In contrast, the MS technique proved more effective in improving the GMI effect, yielding superior results. Co-AWs coated via Ms exhibited smoother surfaces and reduced coercivity. Notably, the GMI effect increased with the thickness of the sputtered carbon coatings, reaching a maximum GMI effect of 522% (a remarkable 357% enhancement) and a sensitivity of 33.8%/Oe at a coating thickness of 334 nm. The observed trend in the GMI effect with carbon layer thickness corresponded closely to variations in transverse permeability, as determined by vibrating sample magnetometry (VSM). Furthermore, the carbon coating induced changes in the initial quenching stress on the surface of the Co-AWs, leading to alterations in impedance and a significant reduction in the characteristic frequency of the Co-AWs. Our findings provide valuable insights into the modulation of GMI properties in Co-AWs, paving the way for their optimized application in advanced magnetic sensor technologies.