Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> • <s> Randomly oriented poly(vinylidene fluoride) (PVDF) nanofibre webs prepared by a needleless electrospinning technique were used as an active layer for making mechanical-to-electrical energy harvest devices. With increasing the applied voltage in the electrospinning process, a higher β crystal phase was formed in the resulting PVDF nanofibres, leading to enhanced mechanical-to-electrical energy conversion of the devices. The power generated by the nanofibre devices was able to drive a miniature Peltier cooler, which may be useful for the development of mechanically driven cooling textile. In addition, the needleless electrospinning also showed great potential in the production of nanofibres on a large scale. <s> BIB001 </s> Energy Harvesting Technologies for Achieving Self-Powered Wireless Sensor Networks in Machine Condition Monitoring: A Review <s> • <s> Recently, a triboelectric generator (TEG) has been invented to convert mechanical energy into electricity by a conjunction of triboelectrification and electrostatic induction. Compared to the traditional electromagnetic generator (EMG) that produces a high output current but low voltage, the TEG has different output characteristics of low output current but high output voltage. In this paper, we present a comparative study regarding the fundamentals of TEGs and EMGs. The power output performances of the EMG and the TEG have a special complementary relationship, with the EMG being a voltage source and the TEG a current source. Utilizing a power transformed and managed (PTM) system, the current output of a TEG can reach as high as 3 mA, which can be coupled with the output signal of an EMG to enhance the output power. We also demonstrate a design to integrate a TEG and an EMG into a single device for simultaneously harvesting mechanical energy. In addition, the integrated NGs can independently output a high voltage and a high current to meet special needs. <s> BIB002
The discovery and selection of energy sources that can be exploited with energy harvesters in mechanical systems is the second challenge. Although the recoverable energy in mechanical systems has been analysed in this paper, the energy losses, mechanical structures and environment for various types of machines are different. This obstacle increases the difficulty of Some investigators are committed to collecting wasted mechanical energy with multiple technology integration. An integrated generator, consisting of six acrylic hexagonal prisms, a cylindrical mass and a magnet (working as six triboelectric harvesters and an electromagnetic one), is designed and installed on an automobile wheel to convert rotational energy of the wheel into electricity in BIB002 . In addition, some engineers designed a system to harvest vibrational, thermal and light energy for establishing a rotating machine monitoring system based on acoustic emission signals BIB001 . ZigBee was selected as the transmission technology in this instance. Most of the models reviewed in this section are designed for monitoring the condition of machine systems with self-powered WSNs. However, the application of EH technologies in other fields is much more practical and prevalent. These designs can give some inspiration for applications of the individual or hybrid EH technologies in machine condition monitoring systems. It can be confirmed that ZigBee is utilized as a transmission method at a higher reliability now. But with the development of Wi-Fi and BLE, especially BLE 5, they will dominate in the market of machine condition monitoring in the future because they have advantages of low power consumption, fast transmission speed, long transmission distance, low cost and high stability. The discovery and selection of energy sources that can be exploited with energy harvesters in mechanical systems is the second challenge. Although the recoverable energy in mechanical systems has been analysed in this paper, the energy losses, mechanical structures and environment for various types of machines are different. This obstacle increases the difficulty of the energy harvesting estimation. It is necessary to design adaptive energy harvesting devices or systems for a variety of applications of monitoring different machines. The next challenge is the improvement and optimization of EH technologies and devices. The energy loss during mechanical operation is mainly dissipated by thermal energy. Both the spatial and the temporal temperature fluctuations are small, and the conversion efficiency of thermal EH technologies is relatively low. Hence the thermal energy harvesting technologies need to be improved to reduce the limitation of temperature cycling techniques and to obtain more effective and efficient energy conversion. Because of the drawbacks of each EH technology, it is necessary to continuously improve the performance of the EH devices by the structural optimization of the systems. For example, it is challenging to design a harvester with an adjustable and flexible structure that can select the optimal frequency band according to the energy distribution of a mechanical system in the frequency domain. The design and optimization of power management circuits is also an important challenge because improving the conversion efficiency of the circuits can effectively and efficiently increase the DC output power, especially for the multi-source energy harvesters. The last challenge is the application of nanomaterials and nanotechnology on energy harvesting (nanogenerators). The emergence of nanomaterials has contributed to the integration of multiple energy harvesting technologies to increase the amount of electricity collected. With the help of nanomaterials, micro-scale wireless sensor nodes can be located inside the machine to acquire more accurate signals because the sensor is closer to the potential fault source and the effect of noise is reduced. However, nanomaterials also face the abrasion and performance degradation of materials like other conventional materials. Therefore, researchers should continue to make efforts to improve the durability and efficiency of nanomaterials to extend the lifespan of the harvesters and realize real maintenance-free WSNs for machine condition monitoring.