We propose an air gap fiber Bragg grating (g-FBG) sensor that can measure strain and temperature simultaneously. The sensor is made by aligning two fiber Bragg gratings (FBGs), and an air gap exists between these two sub-gratings. This sensor’s architecture allows it to form a spectrum with phase-shifted fiber Bragg grating (PSFBG) spectroscopy and Fabry–Perot interference (FPI) spectroscopy. Since the sensitivity of PSFBG and FPI spectra is different for strain and temperature, it is possible to measure both strain and temperature by measuring one of the reflected dips of PSFBG and the interference dip of FPI. The experimental results show that the strain sensitivity is about 11.95 pm/με via the dip wavelength detection of FPI, and the temperature sensitivity is about 9.64 pm/°C via the dip wavelength detection of PSFBG. The g-FBG sensor demonstrates a resolution of approximately ±3.7 με within the strain range of 0 to 1000 με and about ±0.6 °C within the temperature range of 25 °C to 120 °C. The proposed g-FBG sensor, characterized by its simple structure, compact size, and cost-effectiveness, exhibits significant potential in the field of multi-parameter measurements.

This paper aims to develop a resonant accelerometer for high-sensitivity detection and to investigate the nonlinear vibration of the MEMS resonant accelerometer driven by electrostatic comb fingers. First, a nonlinear vibration model of the resonator with comb fingers in a MEMS resonant accelerometer is established. Then, the nonlinear and nonlinear stiffness coefficients are calculated and analyzed with the Galérkin principle. The linear natural frequency, tracking error, and nonlinear frequency offset are obtained by multi-scale method. Finally, to further analyze the nonlinear vibration, a sample-based stochastic model is established, and the uncertainty analysis method is applied. It is concluded from the results that nonlinear vibration can be reduced by reducing the resonant beam length and increasing the resonant beam width and thickness. In addition, the resonant beam length and thickness have more significant effects, while the resonant beam width and the single concentrated mass of comb fingers have little effect, which are verified by experiments. The results of this research have proved that uncertainty analysis is an effective approach in nonlinear vibration analysis and instructional in practical resonant accelerometer design.

A compensation method for nonlinear vibration of a silicon micro resonant sensor is proposed and evaluated to be effective through simulation and experimental analysis. Firstly, the parameter characterization model of the silicon micro resonant sensor is established, which presents significant nonlinearity because of the nonlinear vibration of the resonant beam. A verification circuit is devised to imitate the nonlinear behavior of the model by matching the simulation measurement error of the frequency offset produced by the circuit block with the theoretical counterparts obtained from the model. Secondly, the principle of measurement error compensation is studied, and the compensation method dealing with nonlinear characteristics of the resonant beam is proposed by introducing a compensation beam and corresponding differential operations. The measurement error, compensation rate, and measurement residual between the two scenarios that use single beam and double beams, respectively, are derived and are compared with their simulation and experimental counterparts. The results coincide with the predicted trend, which verifies the effectiveness of the compensation method.

In this paper, based on the multimode interference structure fiber and the sensitive advantages of a zeolitic imidazolate framework-8/Polydimethylsiloxane (ZIF-8/PDMS)-sensitive film in methane detection, a methane sensor based on an interferometer induced by multimode interference is designed and built with the aid of modeling. The methane-sensitive single mode fiber (MS-SMF) is obtained by coating a ZIF-8/PDMS-sensitive film around the cladding of a thin-diameter SMF. The change in methane concentration leads to a change in the cladding mode of the MS-SMF, which causes a change in interference spectrum and realizes methane concentration sensing. The factors affecting the sensitivity of the methane sensor are analyzed. Methane sensors with various parameters are fabricated and tested on a methane sensor platform for performance estimation at methane concentrations of 0–4%. The experimental results show that the sensitivity of the sensor to methane reaches 2.364 nm/% when the length of the MS-SMF is 42 mm, the thickness of the sensitive film is 1.8 µm, and the diameter of the MS-SMF is 58 µm. The limit of detection is about 338 ppm. The average response time is 30 s and the recovery time is 45 s. The temperature sensitivity of the methane sensor is approximately 0.026 nm/°C. The experimental results verify the correctness of the methane sensor model. This study provides a new design idea for optical methane sensors, showing great application potential in the field of methane detection.

A sensitivity-enhanced optical pressure sensor based on molybdenum disulfide (MoS₂) is proposed. The sensing principle is that the pressure causes the deformation of the polydimethylsiloxane (PDMS) pressure structure above the MoS₂ film, leading to the change of the ambient refractive index, so that a measurable light propagation difference in the waveguide under the film is created to reflect the micro changes of the pressure. The pressure is finally numerically converted to the wavelength shift of the interference peak of the obtained spectrum. The process is simulated and analyzed using MoS₂ dielectric film, in contrast with that using graphene dielectric film. It turns out that under same conditions, the MoS₂ film has a more distinct modulation effect on light than that of the graphene film. Experiments using the real sensor prototype are carried out and the results show that the pressure measuring sensitivity is improved to 96.02 nm/kPa in the pressure range of 0–0.6 kPa, which is much higher than the typical optical pressure sensors. The proposed optical pressure sensor based on MoS₂ is of high potential to support ultra-sensitive pressure detection in many applications.

Most current studies on multi-agent evolution based on deep learning take a cooperative equilibrium strategy, while interactive self-learning is not always considered. An interactive self-learning game and evolution method based on non-cooperative equilibrium (ISGE-NCE) is proposed to take the benefits of both game theory and interactive learning for multi-agent confrontation evolution. A generative adversarial network (GAN) is designed combining with multi-agent interactive self-learning, and the non-cooperative equilibrium strategy is well adopted within the framework of interactive self-learning, aiming for high evolution efficiency and interest. For assessment, three typical multi-agent confrontation experiments are designed and conducted. The results show that, first, in terms of training speed, the ISGE-NCE produces a training convergence rate of at least 46.3% higher than that of the method without considering interactive self-learning. Second, the evolution rate of the interference and detection agents reaches 60% and 80%, respectively, after training by using our method. In the three different experiment scenarios, compared with the DDPG, our ISGE-NCE method improves the multi-agent evolution effectiveness by 43.4%, 50%, and 20%, respectively, with low training costs. The performances demonstrate the significant superiority of our ISGE-NCE method in swarm intelligence.