Search

Monitoring and controlling the vibration of bridge cables can maintain the health of the bridge structure and prolong the service life. This work proposes a novel self‐powered intelligent damper (SID) integrated triboelectric‐electromagnetic hybrid unit for vibration in situ monitoring of stay cables. Among them, the sensing function of the SID is realized by an arched membrane triboelectric nanogenerator (AM‐TENG), and the energy harvesting is realized by a three‐phase electromagnetic generator (TP‐EMG). The working principle and performance are investigated. Rotating and linear experimental platforms are built to verify the SID's low‐frequency (0.25–1.50 Hz) performance, including sensing, power generation, and vibration reduction. The experimental result indicates that the fitting vibration speed coefficient of the bridge cable with the AM‐TENG signal frequency is 0.990. In addition, the TP‐EMG achieves a peak power of 1.21 W. At 0.1 A power supply, the SID can output a damping force of 50 N. Finally, an experimental system is constructed to verify the viability of the SID in bridge cable vibration monitoring and vibration reduction. This work provides a feasible solution for further optimizing the bridge structure health monitoring and maintenance system. [ABSTRACT FROM AUTHOR]

The advantages of the triboelectric nanogenerator (TENG) in environmental energy harvesting and utilization determine that they have great development potential in the digital application of power grids. This work focuses on the harvesting and utilization of vibration energy from transmission lines, specifically in the context of breeze vibrations and sub‐span oscillations. To this end, this work proposes a novel multi‐mode vibrational triboelectric nanogenerator (MV‐TENG) and three smart transmission line application strategies based on the MV‐TENG. The MV‐TENG design consists of an S‐beam to broaden the frequency response range by reducing high‐order modal frequencies, and a pair of allegro electrodes to efficiently harvest horizontal and vertical vibration energy. The MV‐TENG demonstrates the capability to harvest vibration energy within a range of 1–3.5 Hz horizontally and 4 Hz, 9–60 Hz vertically, covering the occurrence range of breeze vibrations and sub‐span oscillations of transmission line effectively. Three application strategies include self‐powered tower obstacle alerting, temperature and humidity online monitoring, and high‐temperature wireless warning of transmission lines based on MV‐TENG. In summary, this work presents a comprehensive implementation scheme for digitally integrating TENGs into smart transmission lines, thereby facilitating the engineering development of TENG technology in grid systems. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerator (TENG)'s use is constrained by their surface charge density and alternating current output. This study therefore proposes a coupling output method combining charge excitation and phase shift to realize an almost constant high‐performance direct‐current (DC) and DC‐TENG is designed to harvest the energy of flowing water. The output characteristic of the DC‐TENG with or without charge excitation is thoroughly investigated in the experiment. The impact on the effectiveness of phases (P) and groups (G) is further proven by comparing and quantifying the current wave. The operation capability in a water environment is further demonstrated by the transmitted charge's attenuation of roughly 10.84% after the environment's humidity is increased to 90% RH. According to the findings of the investigation, DC‐TENG with 3P4G can reach almost constant DC with the root mean square value of 29.1 μA and the crest factor of 1.23. And the 220 μF capacitor can be charged to 5 V within 63 s and the peak output power of 9.18 mW is obtained. Finally, an experimental platform is established to simulate the water environment and the thermography is steadily powered. This scheme has reference significance to realize high‐performance DC output in the water environment. [ABSTRACT FROM AUTHOR]

As a microenergy harvesting device, the output performance of triboelectric nanogenerators (TENGs) has long been limited by their surface charges. In this work, an enhancement of the output performance of TENGs via charge clamping (CC‐TENG) is proposed. The device is comprised of a mechanical‐switch direct‐current TENG (MDC‐TENG), charge clamping module (CCM), and main‐TENG. During operation, the CCM is employed to accumulate and clamp the unidirectional charge generated by the MDC‐TENG. And then, the accumulated charges flow between CCM and main‐TENG. With the increase of transferred charges, the output performance can be effectively improved. In addition, the MDC‐TENG is employed to reduce both power dissipation and circuit complexity. Furthermore, an integrated device based on the CC‐TENG is demonstrated which harvests wind energy and attains a charge output of 1.01 µC. Moreover, a multimode coupling is adopted, that is, an alternating‐current TENG operating in contact‐separation mode and a direct‐current TENG operating in a lateral‐sliding mode that can be employed in environments for which multiple motions coexist. The device provides a reference to improve output performance in the context of wind energy capture. [ABSTRACT FROM AUTHOR]

A driver training assistance system (DTAS) is proposed for driver training and behavior monitoring. The DTAS utilizes three driving operation sensors that based on the principle of triboelectric nanogenerators. The gear position sensor can monitor the gear that the driver has switched, the steering angle sensor captures the direction and angle of the driver's rotation of the steering wheel, and the pedal sensor can monitor which pedal the driver is pressing or releasing. In addition, the DTAS can monitor driver behavior and provide feedback on each driver's operation process in real-time. Combined with deep learning (DL) technology, the DTAS can identify and evaluate the results of the driving operation of drivers in specific training scenarios, with an accuracy rate of 97.5%. This work can provide new ideas for the innovative exploration of new driving training modes without coaching and effectively promote the application of triboelectric nanogenerators in the field of intelligent transportation. [Display omitted] • Proposed a driving operation monitoring method that integrates three triboelectric sensors. • The deep learning technology is explored to analyse the driver training electrical signal data. • The developed driving training assistance system can be used to monitor driving behavior and evaluate training results. Improving the driving skills of drivers, particularly during the training stage, is crucial in reducing the likelihood of road traffic accidents. In this work, a driver training assistance system (DTAS) is developed for driver training and behavior monitoring. The DTAS integrates three triboelectric driving operation sensors, including gear shift sensor, steering angle sensor, and pedal sensors. Through the ingenious structural design of contact-separation and freestanding-triboelectric-layer mode, these triboelectric sensors have the characteristics of simple structure, easy manufacture and installation, and self-powered, which avoids the complex wiring problem in the limited space of the vehicle. The basic electrical performance test of triboelectric sensors and driving simulation experiment show that the developed DTAS can monitor the driver behavior and provide the feedback on each driver's operation process in real-time. Combined with deep learning (DL) technology, the DTAS can identify whether the driving operation of drivers in specific training scenarios is correct or not, with an accuracy rate of 97.5%. This work is aimed at assisting the novice or learner drivers in driving training, which helps to improve their driving skills and form good driving habits. The proposed scheme can provide new ideas for the innovative exploration of driving training modes without coaching. [ABSTRACT FROM AUTHOR]

[Display omitted] • A gas-assisted method is proposed for improving the output performance of TENG. • The charge transfer ability of GA-TENG is improved by 13.86 times via the method. • GA-TENG can provide power to wireless sensors and water level detection modules. Triboelectric nanogenerators (TENGs) have unparalleled performance advantages in the low-frequency range and become an emerging technology for efficient wave energy harvesting. There are various methods to improve the output performance of triboelectric nanogenerators, but the output effect and manufacturing convenience of the TENGs cannot be balanced, which limits their promotion and application in a wider field. Here, a gas-assisted triboelectric nanogenerator (GA-TENG) for harvesting wave energy is reported, which has high performance through a gas-assisted method. The gas-assisted device is mainly composed of two airbags and a flexible substrate to increase the actual contact area between the triboelectric layers, which increases the open-circuit voltage (V oc) and transferred charge (Q sc) by 7.99 and 13.86 times, respectively, compared to the rigid substrate. The power density of GA-TENG can reach 20.4 W/m3 under the wave frequency of 1 Hz. In addition, the applications of GA-TENG are successfully demonstrated, including powering three lamps of 3 W, a wireless temperature and humidity sensor, and a water level monitoring module. This work provides a design scheme for wave energy harvesting and a universal method for TENG to harvest renewable energy efficiently. [ABSTRACT FROM AUTHOR]

• An EC-TENG is proposed to achieve a unified conversion of wind and water energy. • Using coupling strategy to unite savonius and pelton turbine with the charge pump. • Coupled power is 442.1% higher than the sum of powers of the main and pump units. • EC-TENG can power wireless sensors at wind and water speeds of 3.5 and 1.3 m/s. As a promising technology, triboelectric nanogenerators (TENGs) can efficiently capture low-frequency energy to power distributed sensors. Wind and water are renewable energy sources that commonly co-exist in the environment, and their simultaneous harvesting has been a hot research topic for TENGs. However, existing researches are essentially the superposition of electrical energy converted from the single energy source, which lack the consideration of the unified conversion of the two energies. Here, we propose an energy-coupled triboelectric nanogenerator (EC-TENG) based on charge pump, which employs a savonius turbine and pelton wheel in conjunction with a system consisting of the main and pump unit to realize the coupling and unified conversion of wind and water energy. The effects on performance of EC-TENG are analyzed theoretically and experimentally. Compared with the sum of the outputs of the main and pump units, the peak power after coupling of the two units is significantly increased by 442.1%. EC-TENG can reach output performances of 7.5 mW and 412.2 mW/m2, and can stably supply power for the wireless temperature and humidity sensor at wind and water speeds of 3.5 m/s and 1.3 m/s, respectively. This work provides a reference for the research of TENGs with multi-energy collection. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel TENGs-based self-powered siphon rain gauge is proposed. • A multi-tube synergistic sensing strategy with TENG is presented for rain measurement. • A potential collection-based generation strategy is utilized for rain energy harvesting. Rainfall measurement is of great significance to agriculture, weather forecasting and water resource management, while rain energy harvesting is a desirable solution to energy demand of wireless sensor networks of rainfall information. In this work, a novel self-powered siphon rain gauge (SR) integrating with a siphon unit, a sensing unit and an energy harvesting unit is proposed, which can simultaneously measure rainfall information and capture rain energy. In the siphon unit, a siphon structure is used to periodically automatically trigger and stop siphon events. In the sensing unit, a liquid–solid multi-tube triboelectric nanogenerator (TENG) is proposed for the first time to detect rainfall information by a multi-tube synergistic sensing strategy. In the energy harvesting unit, a rotary TENG excited by the siphon emptying event is utilized to generate electricity by a rainwater potential energy collection-based generation strategy. After optimization design, the water level resolution of the multi-tube TENG is around 2.5 times higher than that of traditional single-tube TENG, resulting in a rainfall resolution of 20.45 μm of SR. Besides, the rotary TENG successfully converts random, disordered, high-entropy raindrops energy into regular, ordered, low-entropy fluid mechanical energy. It can finally help the SR achieve a power density of 97.2 µW/m2, which is nearly 2.5 times higher than that of liquid–solid contact TENG using the traditional instantaneous impact-based generation strategy. The proposed self-powered SR not only obtains an excellent real-time rainfall sensing capability, but also has remarkable rain energy harvesting ability. Therefore, this SR has great potential for extensive applications in the hydrology and meteorology fields. [ABSTRACT FROM AUTHOR]