Search Results (48)

The inter-shaft bearing is an important component of aero-engine rotor systems. It works between a high-pressure rotor and a low-pressure rotor. Effective fault diagnosis of it is significant for an aero-engine. The casing vibration signals can promptly and intuitively reflect changes in the operational health status of an aero-engine’s support system. However, affected by a complex vibration transmission path and vibration of the dual-rotor, the intrinsic vibration information of the inter-shaft bearing is faced with strong noise and a dual-frequency excitation problem. This excitation is caused by the wide span of vibration source frequency distribution that results from the quite different rotational speeds of the high-pressure rotor and low-pressure rotor. Consequently, most existing fault diagnosis methods cannot effectively extract inter-shaft bearing characteristic frequency information from the casing signal. To solve this problem, this paper proposed the denoised improved envelope spectrum (DIES) method. First, an improved envelope spectrum generated by a spectrum subtraction method is proposed. This method is applied to solve the multi-source interference with wide-band distribution problem under dual-frequency excitation. Then, an improved adaptive-thresholding approach is subsequently applied to the resultant subtracted spectrum, so as to eliminate the influence of random noise in the spectrum. An experiment on a public run-to-failure bearing dataset validates that the proposed method can effectively extract an incipient bearing fault characteristic frequency (FCF) from strong background noise. Furthermore, the experiment on the inter-shaft bearing of an aero-engine test platform validates the effectiveness and superiority of the proposed DIES method. The experimental results demonstrate that this proposed method can clearly extract fault-related information from dual-frequency excitation interference. Even amid strong background noise, it precisely reveals the inter-shaft bearing’s fault-related spectral components. Full article

Compared to conventional materials, underwater metamaterials possess numerous advantages in the manipulation of sound waves, which have garnered increasing attention. In terms of composition, commonly studied underwater wideband metamaterials can be classified into solid-phase pentamode metafluid and water–solid coupling metafluid. The concept of multiphase design in pentamode metafluid allows for decoupling the regulation of equivalent density from that of the equivalent bulk modulus, facilitating more convenient structural design. In typical auxetic metamaterial structure designs, the “re-entrant” mechanism is commonly employed; the skeleton is inwardly bent to a certain extent, enabling the design of a low volume-modulus for each cell. Consequently, a novel type of water–solid coupling metafluid is devised by combining the concepts of “multiphase” and “re-entrant”. Firstly, a straight-sided skeleton (referred to as “ss” skeletal) unit cell is designed, and its compression wave frequency band is determined through analysis of its band characteristics and related vibration modes. Subsequently, the “re-entrant” (referred to as “re”) mechanism is introduced into a unit cell, revealing an increase in equivalent density while decreasing the equivalent volume modulus due to this feature. The bent skeleton provides lower bulk modulus, while multiphase (referred to as “mp”) counterweighting offers higher equivalent density; their combination enables designing more impedance-matched metafluid. Then, a unit cell is designed utilizing both “re” and “mp” characteristics. Finally, acoustic performance simulations and analyses verify that both types exhibit excellent broadband water-like properties within the frequency range of 5000–27,000 Hz. In order to further validate the reliability of the design concept, two pairs of underwater metafluid cells with an impedance-matching effect were subsequently developed, demonstrating sound speeds that are half and one-third that of water, respectively. The skeleton thickness of the “re” cell was moderately enhanced compared to that of the straight side cell, thereby presenting an innovative approach for designing robust underwater metafluid cells. Full article

An all-fiber vibration sensor based on the Fabry-Perot interferometer (FPI) is proposed and experimentally evaluated in this study. The sensor is fabricated by introducing a Fabry-Perot cavity to the single-mode fiber using femtosecond laser ablation. The cavity and the tail act together as a cantilever beam, which can be used as a vibration receiver. When mechanical vibrations are applied, the cavity length of the Fabry-Perot interferometer changes accordingly, altering the interference fringes. Due to the low moment of inertia of the fiber optic cantilever beam, the sensor can achieve broadband frequency responses and high vibration sensitivity without an external vibration receiver structure. The frequency range of sensor detection is 70 Hz–110 kHz, and the sensitivity of the sensor is 60 mV/V. The sensor’s signal-to-noise ratio (SNR) can reach 56 dB. The influence of the sensor parameters (cavity depth and fiber tail length) on the sensing performance are also investigated in this study. The sensor has the advantages of compact structure, high sensitivity, and wideband frequency response, which could be a promising candidate for vibration sensing. Full article

Due to the growth of renewable energies, which requires cost reduction and efficiency in terms of structural health assessment, failure prevention, effective maintenance scheduling, and equipment lifespan optimization, in this paper, we propose an Ultra Wideband (UWB)-based accelerometer Sensor Node for low-power applications in offshore platforms. The proposed Sensor Node integrates a high-resolution accelerometer together with an Impulse Radio Ultra-Wideband (IR-UWB) transceiver. This approach enables effective remote monitoring of structural vibrations. This provides an easy-to-install, scalable, and flexible wireless solution without sacrificing robustness and low power consumption in marine environments. Additionally, due to the diverse and highly demanding applications of condition monitoring systems, we propose two modes of operation for the Sensor Node. It can be remotely configured to either transmit raw data for further analysis or process data at the edge. A hardware (HW) description of the proposed Sensor Node is provided. Moreover, we describe the power management strategies implemented in our system at the firmware (FW) level. We show detailed power consumption measurements, including power profiles and the battery-powered autonomy of the proposed Sensor Node. We compare data from a wired acquisition system and the proposed wireless Sensor Node in a laboratory environment.The wired sensor integrated into this acquisition system, fully characterized and tested, is our golden reference. Thus, we validate our proposal. Furthermore, this research work is within the scope of the SUREWAVE Project and is conducted in collaboration with the MARIN Institute, where wave basin tests are carried out to evaluate the behavior of a Floating Photovoltaic (FPV) system. These tests have provided a valuable opportunity to assess the effectiveness of the proposed Sensor Node for offshore platforms and to compare its performance with a wired system. Full article

The pointing and positioning accuracy of precision instruments in aerospace are often disturbed by low-frequency vibrations. An active/passive vibration isolation system is a feasible solution to suppress low-frequency vibrations. However, the vibration isolation performance of the active control strategy is seriously affected by the uncertainty of the system and the difficulty to meet the higher requirements of new-generation equipment. This paper proposes an active composite control (ACC) strategy for vibration isolation systems with uncertainty. The proposed ACC integrates feedforward control based on known systems and feedback control based on the Kalman filter for systems with uncertainty. Further, the derivation and stability analyses of the proposed ACC algorithm are provided, and the influence of system uncertainty on vibration isolation performance based on the proposed ACC is analyzed. Experimental verification is conducted and the experimental results confirm that the proposed ACC can effectively realize the low-frequency and wide-band vibration isolation for the system with uncertainty. Starting from 30 Hz, the vibration isolation performance of the proposed ACC with uncertainty is significantly improved than that of the ACC completely based on a deterministic system model. Full article

This study introduces an innovative model-order reduction (MOR) technique that integrates boundary element and finite element methodologies, streamlining the analysis of wideband vibro-acoustic interactions within aquatic and aerial environments. The external acoustic phenomena are efficiently simulated via the boundary element method (BEM), while the finite element method (FEM) adeptly captures the dynamics of vibrating thin-walled structures. Furthermore, the integration of isogeometric analysis within the finite element/boundary element framework ensures geometric integrity and maintains high-order continuity for Kirchhoff–Love shell models, all without the intermediary step of meshing. Foundational to our reduced-order model is the application of the second-order Arnoldi method coupled with Taylor expansions, effectively eliminating the frequency dependence of system matrices. The proposed technique significantly enhances the computational efficiency of wideband vibro-acoustic coupling analyses, as demonstrated through numerical simulations. Full article

Gear transmission systems are widely used in ship propulsion systems, but, during operations, they produce serious vibration and noise problems, reducing the fatigue life of gears and affecting the performance of ships and the comfort of operators. Taking into account the complex frequencies and vibration components of gear transmission systems, this study conducted wide-band vibration suppression and noise reduction research on a gear transmission system using an integral squeeze film damper (ISFD), providing a novel approach for reducing vibration and noise in gear transmission systems. By conducting a simulation analysis and numerical calculations, the ISFD was analyzed via a static analysis and a dynamic analysis. We developed an experimental platform for reducing vibration and noise in gear transmission systems using sliding bearings, and the experiments were conducted under different speed and load conditions to study the vibration suppression and noise reduction of gears based on the ISFD. The experimental results show that the ISFD has good vibration suppression capabilities for gears at different speeds, with a horizontal vibration reduction of 75.44% and a vertical vibration reduction of 68.48% at 2400 r/min. The ISFD has wide-band vibration suppression capabilities, especially for mesh frequency and twice-mesh frequency, with a vibration reduction of 86.96% or more. Moreover, the ISFD has good vibration suppression capabilities for gears at different load torques, with a reduction of more than 35% in all directions. In addition, the ISFD also has noise reduction capabilities, reducing the gears’ noise by 1.92 dB at different speeds. Full article

Within the context of a smart home, detecting the operating status of appliances in the environment plays a pivotal role, estimating power consumption, issuing overuse reminders, and identifying faults. The traditional contact-based approaches require equipment updates such as incorporating smart sockets or high-precision electric meters. Non-constant approaches involve the use of technologies like laser and Ultra-Wideband (UWB) radar. The former can only monitor one appliance at a time, and the latter is unable to detect appliances with extremely tiny vibrations and tends to be susceptible to interference from human activities. To address these challenges, we introduce HomeOSD, an advanced appliance status-detection system that uses mmWave radar. This innovative solution simultaneously tracks multiple appliances without human activity interference by measuring their extremely tiny vibrations. To reduce interference from other moving objects, like people, we introduce a Vibration-Intensity Metric based on periodic signal characteristics. We present the Adaptive Weighted Minimum Distance Classifier (AWMDC) to counteract appliance vibration fluctuations. Finally, we develop a system using a common mmWave radar and carry out real-world experiments to evaluate HomeOSD’s performance. The detection accuracy is 95.58%, and the promising results demonstrate the feasibility and reliability of our proposed system. Full article

Roller bearings are critical components in various mechanical systems, and the timely detection of potential failures is essential for preventing costly downtimes and avoiding substantial machinery breakdown. This research focuses on finding and verifying a robust method that can detect failures early, without creating false positive failure states. Therefore, this paper introduces a novel algorithm for the early detection of roller bearing failures, particularly tailored to high-precision bearings and automotive test bed systems. The featured method (AFI—Advanced Failure Indicator) utilizes the Fast Fourier Transform (FFT) of wideband accelerometers to calculate the spectral content of vibration signals emitted by roller bearings. By calculating the frequency bands and tracking the movement of these bands within the spectra, the method provides an indicator of the machinery’s health, mainly focusing on the early stages of bearing failure. The calculated channel can be used as a trend indicator, enabling the method to identify subtle deviations associated with impending failures. The AFI algorithm incorporates a non-static limit through moving average calculations and volatility analysis methods to determine critical changes in the signal. This thresholding mechanism ensures the algorithm’s responsiveness to variations in operating conditions and environmental factors, contributing to its robustness in diverse industrial settings. Further refinement was achieved through an outlier detection filter, which reduces false positives and enhances the algorithm’s accuracy in identifying genuine deviations from the normal operational state. To benchmark the developed algorithm, it was compared with three industry-standard algorithms: VRMS calculations per ISO 10813-3, Mean Absolute Value of Extremums (MAVE), and Envelope Frequency Band (EFB). This comparative analysis aimed to evaluate the efficacy of the novel algorithm against the established methods in the field, providing valuable insights into its potential advantages and limitations. In summary, this paper presents an innovative algorithm for the early detection of roller bearing failures, leveraging FFT-based spectral analysis, trend monitoring, adaptive thresholding, and outlier detection. Its ability to confirm the first failure state underscores the algorithm’s effectiveness. Full article

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile, objective wearable device for remote patient monitoring (RPM) could offer pre-emptive, accurate respiratory data to patients. With this goal as our aim, we used a low-profile accelerometer-based wearable system that utilizes deep learning to objectively detect wheezing along with respiration rate using a single sensor. The miniature patch consists of a sensitive wideband MEMS accelerometer and low-noise CMOS interface electronics on a small board, which was then placed on nine conventional lung auscultation sites on the patient’s chest walls to capture the pulmonary-induced vibrations (PIVs). A deep learning model was developed and compared with a deterministic time–frequency method to objectively detect wheezing in the PIV signals using data captured from 52 diverse patients with respiratory diseases. The wearable accelerometer patch, paired with the deep learning model, demonstrated high fidelity in capturing and detecting respiratory wheezes and patterns across diverse and pertinent settings. It achieved accuracy, sensitivity, and specificity of 95%, 96%, and 93%, respectively, with an AUC of 0.99 on the test set—outperforming the deterministic time–frequency approach. Furthermore, the accelerometer patch outperforms the digital stethoscopes in sound analysis while offering immunity to ambient sounds, which not only enhances data quality and performance for computational wheeze detection by a significant margin but also provides a robust sensor solution that can quantify respiration patterns simultaneously. Full article

This research is dedicated to developing an automatic landing system for shipborne unmanned aerial vehicles (UAVs) based on wireless precise positioning technology. The application scenario is practical for specific challenging and complex environmental conditions, such as the Global Positioning System (GPS) being disabled during wartime. The primary objective is to establish a precise and real-time dynamic wireless positioning system, ensuring that the UAV can autonomously land on the shipborne platform without relying on GPS. This work addresses several key aspects, including the implementation of an ultra-wideband (UWB) circuit module with a specific antenna design and RF front-end chip to enhance wireless signal reception. These modules play a crucial role in achieving accurate positioning, mitigating the limitations caused by GPS inaccuracy, thereby enhancing the overall performance and reception range of the system. Additionally, the study develops a wireless positioning algorithm to validate the effectiveness of automatic landing on the shipborne platform. The platform’s wave vibration is considered to provide a realistic landing system for shipborne UAVs. The UWB modules are practically installed on the shipborne platform, and the UAV and the autonomous three-body vessel are tested simultaneously in the outdoor open water space to verify the functionality, precision, and adaptability of the proposed UAV landing system. Results demonstrate that the UAV can autonomously fly from 200 m, approach, and automatically land on the moving shipborne platform without relying on GPS. Full article

FeSiAl flakes were fabricated by vibrating ball milling the FeSiAl ribbons. And the microwave absorption properties of FeSiAl flakes were improved by doping the multi-wall carbon nanotubes (MWCNTs) with different mass concentrations. The results show that the FeSiAl/MWCNT composites exhibit significantly improved microwave absorption performance with advantages of strong and broadband absorption in the L-band and S-band. In particular, the reflection loss (RL) of the FeSiAl/MWCNT2 composite reaches −7.4 dB at 1.0 GHz, whereupon, through the electromagnetic simulation software CST Microwave Studio, FeSiAl/MWCNT2 all-dielectric metamaterial absorbers (ADMMAs) were macroscopically designed, achieving an ultra-wideband absorption (RL ≤ −10 dB) of 14.4 GHz (3.6~18.0 GHz). It is recognized that the standing wavelength resonance and diffraction effect are responsible for absorbing electromagnetic waves, and the broadband absorption is improved via dielectric dispersion; their synergistic effect makes the ADMMAs exhibit good microwave absorption performance. This work provides a useful method for designing microwave absorption materials with broadband absorption. Full article

Wind turbines (WT) are a popular method used in energy production, but blade failure and maintenance costs pose significant challenges for the industry. Early detection of blade defects is vital to prevent collapse. This paper examines the modulation of blade vibrations via low-frequency blade rotation, mirroring the vibro-acoustic modulation (VAM) method. Specifically, we study the modulation of blade vibrations, which are generated via blade interactions with air turbulence and have a wide frequency range. These vibrations are modulated by the alternating bending stress experienced during blade rotation. For the simulation of VAM, we employ a simple breathing crack model, which considers a mechanical oscillator with parameters that are periodically changed in response to low-frequency blade rotation. The modulation of the wideband signal by blade rotation can be extracted using the detection of envelope modulation on noise (DEMON) algorithm. This model was applied for the estimation of the modulation of a large (52-m-long) WT blade. Steel specimens have been used in laboratory experiments to demonstrate the feasibility of VAM using a probe broadband noise signal. This paper presents the first work to experimentally and theoretically apply wideband signals in VAM. It further explores the analysis of the use of natural vibrations within VAM for the SHM of WT blades. Full article

In this paper, a radial gradient seismic metamaterial (RGSM) is proposed. The structural unit cell is composed of an external square soil embedded with a triangular-cross-sectioned steel ring, which is filled at different angles of multiple steel rings to form a supercell. The dispersion curve and attenuation spectrum of the unit cell are calculated by the finite element method, and the opening mechanism of the band gap is explained by analyzing the modes at the band gap boundary. The influence of geometric parameters and material parameters on the band gap is further studied, and the optimized supercell radial gradient seismic metamaterial (OS-RGSM) structure is designed through structure and parameter optimization. The ultra-low broadband excellent band gap in the range of 2.35–20 Hz for seismic Lamb waves is realized, and its three-dimensional frequency response and displacement field diagram are calculated. In addition, the attenuation characteristics of the optimized supercell seismic metamaterial on the seismic surface wave are calculated and analyzed. It is found that the attenuation can reach more than 50% in the ultra-low frequency range of 3.5–9 Hz. The seismic wave barrier is verified by the vibration transmission characteristics of RGSM under finite period and dynamic time history analysis. The results show that RGSM can effectively shield from seismic Lamb waves in the ultra-wideband with the starting frequency of 2.35 Hz and can also effectively attenuate the seismic surface wave in semi-infinite space. Full article

This paper presents a method for the identification of control-related signal paths dedicated to a semi-active suspension with MR (magnetorheological) dampers, which are installed in place of standard shock absorbers. The main challenge comes from the fact that the semi-active suspension needs to be simultaneously subjected to road-induced excitation and electric currents supplied to the suspension MR dampers, while a response signal needs to be decomposed into road-related and control-related components. During experiments, the front wheels of an all-terrain vehicle were subjected to sinusoidal vibration excitation at a frequency equal to 12 Hz using a dedicated diagnostic station and specialised mechanical exciters. The harmonic type of road-related excitation allowed for its straightforward filtering from identification signals. Additionally, front suspension MR dampers were controlled using a wideband random signal with a 25 Hz bandwidth, different realisations, and several configurations, which differed in the average values and deviations of control currents. The simultaneous control of the right and left suspension MR dampers made it necessary to decompose the vehicle vibration response, i.e., the front vehicle body acceleration signal, into components related to the forces generated by different MR dampers. Measurement signals used for identification were taken from numerous sensors available in the vehicle, e.g., accelerometers, suspension force and deflection sensors, and sensors of electric currents, which control the instantaneous damping parameters of MR dampers. The final identification was carried out for control-related models evaluated in the frequency domain and revealed several resonances of the vehicle response and their dependence on the configurations of control currents. In addition, the parameters of the vehicle model with MR dampers and the diagnostic station were estimated based on the identification results. The analysis of the simulation results of the implemented vehicle model carried out in the frequency domain showed the influence of the vehicle load on the absolute values and phase shifts of control-related signal paths. The potential future application of the identified models lies in the synthesis and implementation of adaptive suspension control algorithms such as FxLMS (filtered-x least mean square). Adaptive vehicle suspensions are especially preferred for their ability to quickly adapt to varying road conditions and vehicle parameters. Full article