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A range of optical fibre-based sensors for the measurement of ethanol, primarily in aqueous solution, have been developed and are reviewed here. The sensing approaches can be classified into four groups according to the measurement techniques used, namely absorption (or absorbance), external interferometric, internal fibre grating and plasmonic sensing. The sensors within these groupings can be compared in terms of their characteristic performance indicators, which include sensitivity, resolution and measurement range. Here, particular attention is paid to the potential application areas of these sensors as ethanol production is globally viewed as an important industrial activity. Potential industrial applications are highlighted in the context of the emergence of the internet of things (IoT), which is driving widespread utilization of these sensors in the commercially significant industrial and medical sectors. The review concludes with a summary of the current status and future prospects of optical fibre ethanol sensors for industrial use.

The most common failures of belt conveyors are runout, coal piles and longitudinal tears. The detection methods for longitudinal tearing are currently not particularly effective. A key study area for minimizing longitudinal belt tears with the advancement of machine learning is how to use machine vision technology to detect foreign items on the belt. In this study, the real-time detection of foreign items on belt conveyors is accomplished using a machine vision method. Firstly, the KinD++ low-light image enhancement algorithm is used to improve the quality of the captured low-quality images through feature processing. Then, the GridMask method partially masks the foreign objects in the training images, thus extending the data set. Finally, the YOLOv4 algorithm with optimized anchor boxes is combined to achieve efficient detection of foreign objects in belt conveyors, and the method is verified as effective.

It is of great significance to develop ethanol sensors with high sensitivity and low detection temperature. Hence, we prepared Au-supported material on mesoporous ZnO composites derived from a metal-organic framework ZIF-8 for the detection of ethanol gas. The obtained Au/ZnO materials were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (SEM), field emission transmission electron microscopy (TEM) and nitrogen adsorption and desorption isotherms. The results showed that the Au/ZnO-1.0 sample maintains a three-dimensional (3D) dodecahedron structure with a larger specific surface area (22.79 m2 g−1) and has more oxygen vacancies. Because of the unique ZIF structure, abundant surface defects and the formation of Au-ZnO Schottky junctions, an Au/ZnO-1.0 sensor has a response factor of 37.74 for 100 ppm ethanol at 250 °C, which is about 6 times that of pure ZnO material. In addition, the Au/ZnO-1.0 sensor has good selectivity for ethanol. According to density functional theory (DFT) calculations, the adsorption energy of Au/ZnO for ethanol (−1.813 eV) is significantly greater than that of pure ZnO (−0.217 eV). Furthermore, the adsorption energy for ethanol is greater than that of other gases.

The Maglev motor has the characteristics of high-speed and high-power density, and is widely used in compressors, molecular pumps and other high-speed rotating machinery. With the requirements of miniaturization and high speed of rotating machinery, the rotor of the maglev motor will operate above the bending critical speed, and the critical vibration control of the flexible rotor is facing challenges. In order to solve the problem of the critical vibration suppression of the maglev high-speed motor, the system model of the maglev motor is established, the rotordynamics of the flexible rotor are analyzed and the rotor model is modal truncated to reduce the order. Then, the μ–controller is designed, and the weighting functions are designed to deal with the modal uncertainty. Finally, an experimental platform of the maglev motor with the flexible rotor is built to verify the effect of the μ–control on the suppression of the critical vibration of the maglev rotor.

A device composed of a piezoelectric bimorph cantilever and a water electrolysis device was fabricated to realize piezoelectrochemical hydrogen production. The obvious output of the hydrogen and oxygen through application of a mechanical vibration of ~0.07 N and ~46.2 Hz was observed. This method provides a cost-effective, recyclable, environment-friendly and simple way to directly split water for hydrogen fuels by scavenging mechanical waste energy forms such as noise or traffic vibration in the environment.

Self-powering electronics by harvesting mechanical energy has been widely studied, but most self-powering processes require a long time in the energy harvesting procedure, resulting in low efficiency or even system failure in some specific applications such as instantaneous sensor signal acquisition and transmission. In order to achieve efficient self-powered sensing, we design and construct an instantaneous self-powered sensing system, which puts heavy requirements on generator’s power and power management circuit. Theoretical analysis and experimental results over two types of generators prove that the planar-structured rotary triboelectric nanogenerator possesses many advantages over electromagnetic generator for the circumstances of instantaneous self-powering. In addition, an instantaneous driving mode power management circuit is also introduced showing advanced performance for the instantaneous self-powering sensing system. As a proof-of-concept, an integrated instantaneous self-powered sensing system is demonstrated based on Radio-Frequency transmission. This work demonstrates the potential of instantaneous self-powered sensing systems to be used in a wide range of applications such as smart home, environment monitoring, and security surveillance.

Air velocity of coal mine ventilation is an important consideration that may cause serious damage. This paper proposes a simple, low cost and effective air velocity monitor (AVM) for coal mine ventilation. The AVM uses the lock-in characteristic of vortex-induced vibration (VIV) to sense the air velocity. Amplitude of the VIV is converted into frequency signal of a vortex-induced triboelectric nanogenerator (VI-TENG) to improve the durability. Structure of the AVM are designed, and parameters of the AVM are optimized with experiments. For the upper and lower air velocity thresholds of 3.1 and 3.6 m/s, the optimized flexible beam length, slider weight, electrode space and electrode width are 42.5 mm, 0.4 g, 0.2 mm and 0.5 mm, respectively. Experiments also show that the output frequency of the VI-TENG could represent the amplitude of VIV well with the correlation coefficient of 0.93. Durability test demonstrates that the AVM generates stable output frequency in 120,000 cycles. A prototype and its controller are fabricated. Wind tunnel tests of this prototype show that it can give alarm when the gas velocity goes above the upper threshold or below the lower threshold. The proposed AVM could be a good solution for simple and effective coal mine ventilation alarm.