Vibration in mechanical equipment can serve as a sustainable energy source to power sensors and devices if it can be effectively collected. In this work, a honeycomb structure inspired triboelectric nanogenerator (HSI‐TENG) consisting of two copper electrode layers with sponge bases and one honeycomb frame filled with polytetrafluoroethylene (PTFE) balls is proposed to harvest vibration energy. The application of a compact honeycomb structure increases the maximum power density of HSI‐TENG by 43.2% compared to the square grid structure and provides superior advantages in large‐scale manufacturing. More importantly, the nonspring‐assisted HSI‐TENG can generate electricity once the PTFE balls obtain sufficient kinetic energy to separate from the bottom electrode layer regardless of the vibration frequency and direction. This is fundamentally different from the spring‐assisted harvesters that can only work around their natural frequencies. The vibration model and working criteria of the HSI‐TENG are established. Furthermore, the HSI‐TENG is successfully used to serve as a self‐powered sensor to monitor engine conditions by analyzing the electrical output of the HSI‐TENG installed on a diesel engine. Therefore, the nonspring‐assisted HSI‐TENG provides a novel strategy for highly effective vibration energy harvesting and self‐powered machinery monitoring.

Inductive wear debris sensor has been widely used in real time machine lubricant oil condition monitoring and fault forecasting. However, the small sensing zone, which is designed for high sensitivity, of the existing sensors leads to low throughput. In order to improve the throughput, a novel multichannel wear debris sensor that is based on phase division multiplexing is presented. By introducing the phase shift circuit into the system, multiple sensing coils could work at different initial phases. Multiple signals of sensing coils could be combined into one output without information loss. Synchronized sampling is used for data recording, and output signals of multiple sensing coils are extracted from the recorded data. A four-channel wear debris sensor system was designed to demonstrate our method. Subsequently, crosstalk analysis, pseudo-dynamic testing and dynamic testing were conducted to check the sensing system. Results show that signals of four sensing coils could be simultaneously detected and the detection limit for ferrous wear debris is 33 μm. Using the presented method, real time wear debris detection in multiple channels could be achieved without increasing the number of excitation source and data acquisition equipment.

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Harvesting acoustic energy in the environment and converting it into electricity can provide essential ideas for self-powering the widely distributed sensor devices in the age of the Internet of Things. In this study, we propose a low-cost, easily fabricated and high-performance coniform Helmholtz resonator-based Triboelectric Nanogenerator (CHR-TENG) with the purpose of acoustic energy harvesting. Output performances of the CHR-TENG with varied geometrical sizes were systematically investigated under different acoustic energy conditions. Remarkably, the CHR-TENG could achieve a 58.2% higher power density per unit of sound pressure of acoustic energy harvesting compared with the ever-reported best result. In addition, the reported CHR-TENG was demonstrated by charging a 1000 μF capacitor up to 3 V in 165 s, powering a sensor for continuous temperature and humidity monitoring and lighting up as many as five 0.5 W commercial LED bulbs for acoustic energy harvesting. With a collection features of high output performance, lightweight, wide frequency response band and environmental friendliness, the cleverly designed CHR-TENG represents a practicable acoustic energy harvesting approach for powering sensor devices in the age of the Internet of Things.

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