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Prognostics and health management (PHM) has developed into a crucial discipline because of its never-ending pursuit of safety, effectiveness, and dependability. The aircraft Landing gear (LG) is one of the most significant components during takeoff and landing. Consequently, the PHM of LG is essential for the aircraft to operate safely and reliably. This paper provides an in-depth exploration of the developments, difficulties, and prospects in PHM for aircraft LG. The study begins by providing an overview of the LG parts and related faults, emphasizing their importance for the flight safety. The insights of PHM are presented based on various artificial intelligence (AI) techniques. Various approaches are discussed for fault detection and isolation (FDI) and remaining useful life (RUL). These efforts help to improve the maintenance and decision-making (MDM) process, which improves the overall effectiveness of PHM. With the aim of giving researchers a useful resource, this review addresses to fill the research gaps based on the available literature so far. It lays the foundations for future advancements by highlighting the challenges in this field.

Hydraulic cylinders are typical actuators that are used in many industries, including manufacturing and construction machinery. Due to the wide application of cylinders, cylinder failures could increase maintenance costs, reduce productivity, and raise safety issues. Therefore, estimating and predicting the condition of cylinders is necessary for cost reduction and safety. This paper reviews various methods that have been proposed to estimate and predict cylinder failures. The paper first investigates the types of failures that can occur in cylinders and their causes. The failures include internal leakage, external leakage, and seal wear. The sensors used to identify each type of failure are then introduced. Since the failure information of the cylinder is implicitly embedded in the measured data, different diagnostics methods for isolating the failure information have been developed for each sensor. The diagnostic methods vary from traditional feature engineering to recent artificial intelligence-based methods. The prognostics that provide the remaining useful life of the cylinder are then reviewed. Finally, the paper discusses the challenges associated with the fault prognosis of hydraulic cylinders and future prospects.

One representative feature of a locally resonant elastic metamaterial (LREM) is that they can prohibit elastic wave propagation at the frequencies inside a band gap, which means that no energy is transmitted. When an incident wave propagates in a host medium at the frequencies inside band gaps, the incident wave is totally reflected at the interface between the host medium and an LREM. However, it remains unexplored what kind of mechanical boundary (e.g. fixed or free) is formed at the interface between the host medium and the LREM. This study thus aims at finding design principles for effective mechanical boundary (EMB) formation and validating the principles by numerical simulation. Conditions for certain EMBs were derived from the magnitude and phase of the reflection coefficient of the LREM. According to the conditions, an LREM is designed and attached to a host medium. It was confirmed from time-harmonic simulation that the velocity at the interface between the host medium and the LREM approached zero when the effective fixed boundary is formed, while the stress at the interface approached zero when the effective free boundary is formed.Graphical Abstract

A phononic crystal (PnC) is an artificially engineered periodic structure that exhibits extraordinary phenomena, such as a phononic band gap. The phononic band gap refers to a certain range of frequencies within which mechanical waves cannot propagate through the PnC. The main purpose of this paper is to propose a topology optimization formulation for phononic band gap maximization that simultaneously takes into account a target driving frequency. In the proposed topology optimization formulation, a relative band gap is considered as an objective function to be maximized. In addition, an equality constraint is imposed on the central frequency of the band gap. The topology optimization problem is solved using the globally convergent method of moving asymptotes, which is a gradient-based optimization algorithm. Numerical examples are computed to demonstrate the effectiveness of the proposed topology optimization formulation.

Piezoelectric energy harvesting at multi-scales has received considerable attention as an attractive powering technology which enables sustainable self-powered operation of small electronics such as wireless sensors. Self-powered wireless sensors for structural health monitoring, biomedical and wearable applications would be great potential applications with high market demand. A key challenge has been insufficient power generation for practical applications, which necessitates a new paradigm in the design of energy harvesting systems. In this work, drastic enhancement of harvesting performance along with energy focusing is demonstrated both analytically and experimentally by introducing metamaterial-based energy harvesting (MEH) systems. Metamaterials, artificially engineered structures, exhibit unique properties including band gap and negative refractive index and thus enable us to manipulate mechanical wave propagations. Wave guide and localization toward a desired position can lead to amplification of harvestable input mechanical energy. In this work, systematic design of two-dimensional octagonal phononic crystals (PnCs) through geometric and band gap optimization process is proposed and followed by experimental demonstration. Energy confinement and localization at the defect of proposed PnCs leads to successful enhancement of harvesting power up to 22.8 times compare to the case without the presence of metamaterial.

A critical challenge in energy harvesting has been insufficient sustainable power generation for practical applications, despite the benefits of self-powering and green-enabling technology. Metamaterials are artificial structures capable of controlling and manipulating functionalities beyond the limit of natural materials. Various metamaterial concepts including phononic crystals (PnCs) and locally resonant metamaterials have proved to manipulate mechanical waves and enable amplification of input mechanical wave energy, such as sound, vibration, and ultrasonic waves, thus enabling drastic enhancement of energy harvesting thus far. Along with the need for research on novel metamaterial designs for energy localization and focusing, fundamental understanding of the energy transfer and conversion at the interface between the piezoelectric energy harvesting (PEH) devices and the metamaterial host structure is also crucial to further enhancing the output power performance of metamaterial-based energy harvesting. Here, we report a substantially enhanced harvesting power amplification and output power in phononic crystal-assisted elastic wave energy harvesting by tailoring geometric and materials parameters of a PEH device for a given PnC structure. We envision that the underlying wave physics and materials science in this rational parametric design strategy will contribute to realizing self-powered sensor applications in industrial and environmental monitoring fields.