Structural vibrations usually exist in the form of low-frequency and broadband elastic waves, so cantilever-like harvesters are not appropriate due to space limitations and high quality factor. Piezoelectric metamaterial plate with local resonators (PMP-LR) has been explored to overcome it. However, how to model and analyze the whole energy harvesting system is still a challenge. In this paper, a self-powered

The present work deals with multi-layer rectangular core topology systems built up by stacking layers made of different rectangular core geometries. Multi-layer systems have been intensively studied in terms of mechanical performances whereas their vibroacoustic behavior, acoustic efficiency and design is however still an open issue. Several design parameters should be considered to fully understand

This paper develops a transient wave-based method to estimate the viscoelastic parameters (VEPs) of a pipe where unknown leaks may exist. The proposed method exploits the fact that the time instants at which the transient pressure signal crosses the steady-state pressure signal is independent of leaks and dependent on VEPs. It is demonstrated that the resulting optimization problem is convex, i.e.

In this study, we propose a new approach for novelty detection that uses kernel dependence techniques for characterizing the statistical dependencies of random variables (RV) and use this characterization as a basis for making inference. Considering the statistical dependencies of the RVs in multivariate problems is an important challenge in novelty detection. Ignoring these dependencies, when they

In the present paper, two existing nonlinear system identification methodologies are used to identify data-driven models. The first methodology focuses on identifying the system using steady-state excitations. To accomplish this, a phase-locked loop controller is implemented to acquire periodic oscillations near resonance and construct a nonlinear-mode model. This model is based on amplitude-dependent

In the context of control of smart structures, we present an approach for state estimation of adaptive buildings with active load-bearing elements. For obtaining information on structural deformation, a system composed of a digital camera and optical emitters affixed to selected nodal points is introduced as a complement to conventional strain gauge sensors. Sensor fusion for this novel combination

This paper proposes a robust lateral control system with fuzzy state observer based on Takagi-Sugeno fuzzy model of autonomous four-wheel independent drive electric vehicles (A-4WDEVs) considering the roll effects and actuator faults. Firstly, a Takagi-Sugeno fuzzy model of A-4WDEVs with uncertainties, time-varying parameters and actuator faults is presented, which can describes the coupling lateral

Despite the recent advances on intelligent data-driven machinery fault diagnostics, large amounts of high-quality supervised data are mostly required for model training. However, it is usually difficult and expensive to collect sufficient labeled data in real industries, and the difficulty in data preparation significantly hinders the application of the intelligent diagnostic methods. In order to address

In present work the stability and coupling dynamic characteristics for a vibrating system with one internal degree of freedom, driven by two vibrators, are investigated, which is a further extension and innovation of a previous literature. In theory, the responses of the relative and absolute motion of the system are given; the synchronization criterion of the system is obtained based on the average

This research uses nonlinear Rayleigh waves to examine different levels of plastic strain in samples made from legacy X52 pipeline material. Here the plastic strain is used as a surrogate for the damage associated with a pipeline dent. Tension specimens are subjected to a static, mechanical load. Nonlinear Rayleigh waves are used to measure the relative acoustic nonlinearity parameter, β′ in these

Leak detection is critical for the safety management of pipelines since leakages may cause serious accidents. The present paper aims to develop an efficient method able to detect the presence and importance of leaks in pipelines. This method relies on adequate signal processing of acoustic emission (AE) signals, and improves the variational mode decomposition (VMD) for signal de-noising. In order to

As a new gear processing technology, gear slicing technology has the characteristics of high efficiency, high precision and environmental protection. In this paper, the slicing process with equal-rake angle arc-tooth slice tool (ERA-ATST) is taken as the research object. Considering the particularity of the slicing process, a theoretical calculation method of tool and chip temperature is proposed.

The synthesis of structural health monitoring with vibration control is cost-effective and beneficial for developing smart structures. In the last decade, some synthetic algorithms have been proposed for combining system identification and vibration control. Among them, an approach has been developed recently for the synthesis of identification and vibration control under unknown excitation. However

This paper proposes a robust road profile estimation method and vehicle parameter identification method through an optimization with an objective function and constraint conditions on estimated profiles. The methods require only vehicle response measurements, enabling easy and inexpensive, yet effective, road condition monitoring through the automated processing of smartphone data. A half-car (HC)

The Acoustic Emission (AE) phenomenon has been used as a powerful tool with the purpose to either detect, locate or assess damage for a wide range of applications. Derived from its monitoring, one major current challenge on the analysis of the acquired signal is the proper identification and separation of each AE event. Current advanced methods for detecting events are primarily focused on identifying

In recent years, with the development of national economy and the continuous improvement of the electrical level of daily life, various household appliances have gradually entered the field of life. Small circuit breakers have become the most widely used terminal protection equipment in electrical terminal distribution equipment of buildings, its performance plays a key role in the safety of circuits

On the basis of previous research, this paper takes a more comprehensive study on the vibration of a vehicle with automatic transmission when engine start-stop and automatic start-stop. A 13 degrees of freedom (DOFs) vehicle dynamic model is established, and the dynamic response evaluation method is put forward. Three methods to reduce the vibration of powertrain and vehicle are analyzed, and the results

The position tracking problem is investigated in this paper for DC torque motor system. A novel fixed-time control strategy is presented, the structure of which can be adjusted with continuous transition. A fixed-time extended state observer is designed to estimate the total disturbance. The proposed observer-based controller renders the position of DC torque motor track the desired signal in fixed

This paper proposes a saturated output-feedback trajectory tracking controller for an autonomous tractor with N-trailer with guaranteed desired performance specifications. At first, an input-output model of the tractor with N-trailer system is presented by a proper selection of the output variables vector. Based on a prescribed performance technique, a nonlinear transformation between the constrained

This paper proposes an improved optimal integral sliding mode control (IOISMC) for a robust and optimal tracking control of robotic manipulators under the presence of coupling effects, parameter variations, and external disturbances. By representing the system dynamics in the error coordinate and introducing an additional optimal integral term in the nominal control part of IOISMC, the effects of unmeasured

This paper presents a method called subband averaging kurtogram (SAK), incorporating with dual-tree complex wavelet packet transform (DTCWPT), to improve performance of the fast kurtogram (FK) for rotating machinery fault diagnosis. The proposed method first segments a signal into M sub-signals by a sliding window, then computes the kurtosis of subbands obtained by DTCWPT of each sub-signal. Finally

In this paper, an auto-tuning algorithm of model-based feedforward controller by feedback control signal in ultraprecision motion systems is proposed. The algorithm is predicated on the simple fact that for a control system with well-tuned feedback controller, at low frequency range, feedback control signal is a good approximation of the ideal feedforward signal required to achieve perfect tracking

The throttle valve is the core equipment to managed pressure drilling (MPD) technology. PID controller is the most widely used throttle valve control algorithm. However, in the wellhead back pressure control system, the control of the throttle valve has strong nonlinearity and time variability. This makes precise closed-loop control of wellhead back pressure a challenge. The traditional controller

This paper is focused on the application of the fundamental model reduction techniques used in structural dynamics to flexible multibody systems. In particular, an effective computational approach is developed and tested in this work for adapting the conventional structural model condensation strategies to the dynamics of flexible multibody systems. Thereby, the synthesis methods considered in this

Rolling bearing fault diagnosis is a meaningful yet challengeable task. To improve the performance of rolling bearing fault diagnosis, this paper proposes an enhanced selective ensemble deep learning method with beetle antennae search (BAS) algorithm. Firstly, multiple deep base models are constructed to automatically capture sensitive features from raw vibration signals. Secondly, to ensure the diversity

The lateral pulling of tire burst vehicle results in accident and fatality on the highway due to its sudden C.G displacement of the vehicle. Improper steering input leads to detach wheel from vehicle and rollover accident due to the weight transfer towards the flat tire. Therefore, this paper attempts to reduce the lateral velocity and its displacement of the vehicle by producing the force through

Real-time monitoring of instantaneous cable tension is essential for condition monitoring and health diagnosis of cable-supported bridges. Vibration-based identification of cable tension resting on the relation between the cable tension and the frequency of dynamic responses has been increasingly investigated in the last decade. The extant studies have realized identification of cable tension by in-situ

The first order and second order bistable Duffing oscillator are selected as typical models for analyzing the stochastic characteristics of double-well nonlinear oscillators excited by sinusoidal force and Gaussian white noise. By employing cyclostationary Gaussian analysis, two solution modes of the almost low-energy and high-energy oscillations are identified. A criterion is proposed to classify

Uncertainty quantification (UQ) and global sensitivity analysis (GSA) of dynamic characteristics of complex systems subjected to uncertainty are jointly investigated in this paper. An efficient approach based on arbitrary polynomial chaos expansion (aPCE) is presented for analytical, unified implementation of UQ and GSA in structural dynamics. For UQ of dynamic characteristics, statistical moments

One of the latest trends in structural health monitoring involves the use of wireless decentralized sensing systems, developed to reduce costs and speed up the whole monitoring process. The main purpose of this paper is to present a novel decentralized procedure for the instantaneous modal identification of time-varying structures, also suitable in the presence of environmental variations and non-stationary

Gear pitting fault diagnosis has always been an important subject to industry and research community. In the past, the diagnosis of early gear pitting faults has usually been carried out under single gear health state. In order to diagnose the early gear pitting faults with mixed operating conditions and reduce the number of training parameters, a new method is proposed in this paper. The proposed

In this study the use of many stand-alone devices is considered for active vibration control. A stand-alone device represents a control unit which is able to independently perform the vibration control task, since it is embedded with sensors, an inertial actuator and a microcontroller, in which the control algorithm is implemented. The aim of this architecture is to improve the performance of a decentralized

Smart manufacturing is one of the key parts of the fourth industry revolution (Industry 4.0). It offers promising perspectives for high reliability, availability, maintainability and safety production process, but also makes the systems more complex and challenging for health assessment. To deal with these challenges, one needs to develop a robust approach to monitor and assess the system health state

Trackside monitoring of railways provides useful data for understanding the condition and mechanical behaviour of railway track, prior research has shown that railway track performance varies significantly along its length, primarily owing to changing support conditions. Understanding the changing performance along track offers the potential for improved track design and maintenance. Different technologies

Nowadays, with the change of the times, the traditional paper-and-pencil examination can not satisfy the students' test. For students of different levels, it is difficult to say that the best test effect can be achieved by passing the fixed test. In order to test students' level accurately, this paper proposes an adaptive test system based on item response theory, which integrates AI recognition model

The development of a viable structural health monitoring (SHM) technology for the operational condition monitoring of wind turbine blades is of great interest to the wind industry. In order for any SHM technology to achieve the technical readiness and performance required for an operational implementation, advanced signal processing algorithms need to be developed to adaptively remove noise and retain

In order to obtain a precise dynamic structural FE model for dynamic analysis, FE model updating is usually used to correct uncertainty parameters for an initial FE model using incomplete measured data. Despite numerous studies concerning FE model updating, the computational cost is still a challenging issue for the repeated eigenvalue structures. Firstly, an improved modal assurance criterion is proposed

Torque and rotational speed are important parameters to characterize the power of rotating parts for mechanical systems, so a rotational shaft’s torque and rotational speed sensing method and real-time signal processing are key technologies for mechanized equipment, such as vehicles, ships, etc. Hence an advanced torque and speed sensing technology and a data processing technology are very important

To comprehensively understand the decision information system for the information processing of the intelligent manufacturing under Internet of Things, an intelligent decision support system (DSS) based on data mining technology is applied to enterprises to establish an Internet of Things-based intelligent DSS for manufacturing industry, thereby supporting the decision-makers in making intelligent

The analysis presented in this work relates to the quantification of the effect of a selected set of measured Environmental and Operational Parameters (EOPs) on the dynamic properties of low and high frequency vibration, in the context of a vibration monitoring campaign implemented on the blade of an operating wind turbine. To this end, a Gaussian Process (GP) time-series modelling approach is adopted

Performing condition monitoring on rotating machines such as wind turbines, which operate inherently under time-varying operating conditions, remains a challenge. The signal components generated by incipient damage are masked by other signal components that are not of interest and high noise levels. In this work, a new method, referred to as the IFBIαgram, is proposed that is capable of identifying

A novel concept of investigating blade vibration in turbomachinery is presented on the basis of Blade Tip-Timing (BTT) and clearance sensor waveform analysis methods (BLASMA), with which vibration parameters are determined by global optimization. It is shown that the modulation of the sensor output by blade vibration can offer additional information compared with under-sampled time-of-arrival (TOA)

The application of shift cell technique is presented and discussed for periodic porous media described with equivalent fluid models: as it can be found in literature, it consists in a reformulation of classical Floquet-Bloch (F-B) conditions, in which the phase shift of the boundary conditions, related to wave propagation, is integrated into the partial derivative operator. Consequently, the periodicity

Light activated shape memory polymer (LaSMP) is one of novel shape memory polymers with dynamic strain and Young’s modulus when exposed to UV lights. This study investigates distributed microscopic control actions of LaSMP patches on hemispherical shells with free boundary. Based on strain models established in the experiments, governing equations of the spherical shell are defined and control forces

A transient large-amplitude car-body vibration could seriously affect train operational safety and riding comfort when a high-speed train passes through a complex terrain under strong wind conditions. In this study, according to the car-body vibration characteristics under strong wind conditions and the definition of the train overturning coefficient, a railway half-vehicle vibration-overturning analytical

Random fluctuations of the nonlinearity curves of Fabry–Perot (F–P) tunable filters cause instabilities in fiber Bragg grating (FBG) interrogation systems. FBG sensors are widely used in structural health monitoring (SHM), and suppressing random fluctuations can provide engineers with more precise information on the conditions of structures. While F–P etalon and acetylene (C2H2) are most commonly used

With the increasing frequency and intensity of earthquakes, the idea of seismic design continues to develop, and it must be ensured that the structure not only has sufficient strength, but also has certain ductility. However, there is currently no suitable method for effective evaluation of seismic performance. In order to find a method with high accuracy, this paper uses BP neural network algorithm

Feathers are the main raw material of shuttlecock. The quality of feather is a key factor in shuttlecock production and detection of feather defects is a challenging problem. In this paper, an automatic detection for feather defects was proposed that relies on fuzzy, Lie Group and machine learning theory. First, the feather images were enhanced using fuzzy set. Then, a covariance matrix was constructed

With the continuous development of information technology, data resources have become increasingly rich, but the knowledge contained in data resources has not been fully explored and utilized. In order to find an effective computer testing technology, the paper introduces the partial differential equation (PDE) into the denoising process of rotor vibration signal through data mining technology, and

Multispectral filter array (MSFA) imaging with one single sensor is a portable and inexpensive means of acquiring spectral image which is widely used for object detection, material analysis and mechanical system diagnosis. The most challenging task for MSFA imaging is the multispectral demosaicking with the aim of reconstructing the captured raw/mosaic image, especially for the systems with many bands

In recent years, mechanical fault diagnosis technology at home and abroad has developed rapidly, and its application has spread to various industrial fields. Due to the complex structure of rotating machinery, the ambiguity and complexity of fault characteristics and causes are common, and it is difficult to carry out fault diagnosis. Although many researches have been carried out and some research

By using various Internet of Things technologies and communication technologies, smart cities can respond quickly and intelligently to various service requests of cities, thus realizing the intelligent operation and management of cities, strengthening the management of urban facilities and improving the quality of urban services. To improve the operational efficiency of smart car network systems and

The model updating of the electro-mechanical properties of Piezoelectric Energy Harvesters (PEHs) using experimental data within a Bayesian inference setting is discussed. The implementation requires: a predictive model for the harvester response; an assumption for its prediction error; a prior multivariate probabilistic density function for the electromechanical properties; and experimental measurements

Anomaly detection by Mahalanobis-squared distance (MSD) is a popular unsupervised learning approach to structural health monitoring (SHM). Despite the popularity and high applicability of the MSD-based anomaly detection method, some major challenging issues and limitations such as environmental variability, determination of an inappropriate threshold limit, estimation of an inaccurate covariance matrix

In this paper, a new method is proposed to deal with the interval model updating problem using universal grey mathematics and Gaussian process regression model (GPRM). The nonlinear relationship between the input and the output generally exists in the interval model updating problem, which has not been specially discussed in the current papers. In order to handle this issue better, the method concerned

The shape function-based methods are promising in dynamic force identification. However, the selection of shape function is still an issue as it determines the identification accuracy and efficiency to a large extent. This paper proposes a dynamic force identification approach by using the composite trigonometric wavelet as shape function which takes advantage of its 'wave' property in dynamic force

Development of multiple launch rocket system (MLRS) has been restricted for several decades due to the poor dispersion characteristics of rockets, which is caused by the orientation of the MLRS departing from that intended. Hence, it is vital to maintain the angles of MLRS at a desired value via a proper control strategy. In this paper, a new neural network predictive control is developed for orienting

This paper proposes a nonlinear whole-machine dynamic model for a typical bimodal standing wave ultrasonic motor considering nonlinear electroelasticity of piezoelectric vibrator under high excitation voltage. To capture the inherent nonlinearities of the piezoelectric element, nonlinear constitutive relations of piezoelectric element are adopted to derive the nonlinear electromechanical coupling model