Vibration energy harvesting typically involves a mechanical oscillatory mechanism to accumulate ambient kinetic energy, prior to the conversion to electrical energy through a transducer. The convention is to use a simple linear mass-spring-damper oscillator with its resonant frequency tuned towards that of the vibration source. In the past decade, there has been a rapid expansion in research of vibration energy harvesting into various nonlinear vibration principles such as Duffing nonlinearity, bistability, parametric oscillators, stochastic oscillators and other nonlinear mechanisms. The intended objectives for using nonlinearity include broadening of frequency bandwidth, enhancement of power amplitude and improvement in responsiveness to non-sinusoidal noisy excitations. However, nonlinear vibration energy harvesting also comes with its own challenges and some of the research pursuits have been less than fruitful. Previous reviews in the literature have either focussed on bandwidth enhancement strategies or converged on select few nonlinear mechanisms. This article reviews eight major types of nonlinear vibration energy harvesting reported over the past decade, covering underlying principles, advantages and disadvantages, and application-specific guidance for researchers and designers.

A cantilever with an end mass is one of the most popular designs for piezoelectric MEMS vibration energy harvesting. The inclusion of a proof mass near the free end of a micro-cantilever can significantly enhances the power responsiveness of a vibration energy harvester per unit acceleration. However, the accommodation of the proof mass comes at the expense of the active piezoelectric area. This paper numerically and experimentally investigates this compromise, and explores the optimal proof-mass-to-cantilever-length ratio for power maximization. It was found that an end mass occupying about 60%-70% of the total cantilever length is optimal within linear response, and they notably outperform comparable cantilevers with 40% and 50% of end mass. In addition, nonlinear squeeze film air damping within the chip package was found to adversely affect the cantilevers with larger mass more significantly. A harvester prototype with 70% of the length covered by end mass (5 mm ³ ) was able to generate 1.78 μW at 0.6 ms ^-2 and up to 20.5 μW at 2.7 ms ^-2 and 210 Hz when not limited by nonlinear damping. This result outperforms the previously reported counterparts in the literature by nearly an order of a magnitude in terms of power density normalized against acceleration squared.

Piezoelectric vibration energy harvesters have been widely researched and are increasingly employed for powering wireless sensor nodes. The synchronized switch harvesting on inductor (SSHI) circuit is one of the most efficient interfaces for piezoelectric vibration energy harvesters. However, the traditional incarnation of this circuit suffers from a significant startup issue that limits operation in low and variable amplitude vibration environments. This paper addresses this start-up issue for the SSHI rectifier by proposing a new architecture with SSHI startup circuitry. The startup circuitry monitors if the SSHI circuit is operating correctly and re-starts the SSHI interface if required. The proposed circuit is comprehensively analyzed and experimentally validated through tests conducted by integrating a commercial piezoelectric vibration energy harvester with the new interface circuit designed in a 0.35-μm HV CMOS process. Compared to conventional SSHI rectifiers, the proposed circuit significantly decreases the required minimum input excitation amplitude before energy can be harvested, making it possible to extract energy over an increased excitation range.

As the “right-hand man” to space communications, navigation, environmental monitoring, and other satellite systems, the space active phased array antenna is capable of scanning and covering long distances and large scale ranges through its complex deployment mechanism, large physical aperture, and lightweight structural design. In comparison with mechanical scanning antennas, the space active phased array antennas can realize flexible beam scanning through the active phased array principle, while simultaneously achieving a high gain, low sidelobe, high resolution, and high reliability. Improving the comprehensive performance of the satellite is crucial with the rapid development requirement and large application field. In this article, the development history of the space active phased array antennas is summarized, and these antennas are characterized by the following structural features: large aperture, deployment mechanism, and lightweight configuration. The state of the art of space deployable active phased array antennas is also presented. Furthermore, seven crucial design technologies of antenna essential components are discussed, and the development trends of structural technologies of the space deployable active phased array antenna are demonstrated.

Piezoelectric vibration energy harvesting has drawn much interest to power distributed wireless sensor nodes for Internet of Things (IoT) applications where ambient kinetic energy is available. For certain applications, the harvesting system should be small and able to generate sufficient output power. Standard rectification topologies such as the full-bridge rectifier are typically inefficient when adapted to power conditioning from miniaturized harvesters. Therefore, active rectification circuits have been researched to improve overall power conversion efficiency, and meet both the output power and miniaturization requirements while employing a MEMS harvester. In this paper, a MEMS piezoelectric energy harvester is designed and co-integrated with an active synchronized switch harvesting on inductor (SSHI) rectification circuit designed in a CMOS process to achieve high output power for system miniaturization. The system is fully integrated on a nail-size board, which is ready to provide a stable DC power for low-power mini sensors. A MEMS energy harvester of 0.005cm3 size, co-integrated with the CMOS conditioning circuit, outputs a peak rectified DC power of 40.6μ W and achieves a record DC power density of 8.12mW/cm3 when compared to state-of-the-art harvesters.

Helical gearboxes play a critical role in power transmission of industrial applications. They are vulnerable to various faults due to long-term and heavy-duty operating conditions. To improve the safety and reliability of helical gearboxes, it is necessary to monitor their health conditions and diagnose various types of faults. The conventional measurements for gearbox fault diagnosis mainly include lubricant analysis, vibration, airborne acoustics, thermal images, electrical signals, etc. However, a single domain measurement may lead to unreliable fault diagnosis and the contact installation of transducers is not always accessible, especially in harsh and dangerous environments. In this article, a Compressive Sensing (CS)-based Dual-Channel Convolutional Neural Network (CNN) method was proposed to accurately and intelligently diagnose common gearbox faults based on two complementary non-contact measurements (thermal images and acoustic signals) from a mobile phone. The raw acoustic signals were analysed by the Modulation Signal Bispectrum (MSB) to highlight the coupled modulation components relating to gear faults and suppress the irrelevant components and random noise, which generates a series of two-dimensional matrices as sparse MSB magnitude images. Then, CS was used to reduce the image redundancy but retain key information owing to the high sparsity of thermal images and acoustic MSB images, which significantly accelerates the CNN training speed. The experimental results convincingly demonstrate that the proposed CS-based Dual-Channel CNN method significantly improves the diagnostic accuracy (99.39% on average) of industrial helical gearbox faults compared to the single-channel ones.