Showing papers in "Mechanical Systems and Signal Processing in 2014"

TL;DR: A comprehensive review of the PHM field is provided, followed by an introduction of a systematic PHM design methodology, 5S methodology, for converting data to prognostics information, to enable rapid customization and integration of PHM systems for diverse applications.

TL;DR: In this paper, various mathematical models for hysteresis such as Preisach, Krasnosel’skii-Pokrovskii (KP), Prandtl-Ishlinskii (PI), Maxwell-Slip, Bouc-Wen and Duhem are surveyed in terms of their applications in modeling, control and identification of dynamical systems.

TL;DR: In this paper, an ensemble empirical mode decomposition (EEMD) is applied on the low Q-factor transient impact component and satisfactory extraction result is obtained, and the original signal of rolling bearing early weak fault is decomposed by EEMD and several intrinsic mode functions (IMFs) are obtained.

TL;DR: In this paper, the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal were analyzed for the diagnostics of bearing failures.

TL;DR: In this article, the authors proposed a new method for gear fault detection under time-varying rotational speed without using a tachometer, which consists of four main steps: (a) signal filtering via fast spectral kurtosis (SK) analysis, (b) extraction of instantaneous fault characteristic frequency (IFCF) from the TFR using an amplitude-sum based spectral peak search algorithm, (c) signal resampling based on the extracted IFCF to convert the non-stationary time-domain signal into the stationary fault phase angle (F

TL;DR: In this paper, a diagnostic approach is proposed for bearing used in wind turbines, which uses parameters obtained from commercial diagnostic system (peak-to-peak and root mean square (RMS) of vibration acceleration, and generator power that is related to the operating conditions).

TL;DR: In this article, a hybrid approach for characterizing fatigue damage was developed, using two genres of damage indices constructed based on the linear and the nonlinear features of acousto-ultrasonic waves.

TL;DR: In this paper, a semi-active vibration absorber with real-time controlled magnetorheological damper (MR-SVA) is presented for the mitigation of harmonic structural vibrations.

TL;DR: In this paper, the synergy between a wavelet transform (WT) and a Teager energy operator (TEO) is explored, with the aim of ameliorating the curvature mode shape.

TL;DR: Wang et al. as discussed by the authors proposed a novel output-only damage identification method based on the unsupervised blind source separation (BSS) technique termed independent component analysis (ICA), which is discovered that ICA biases to extract sparse component, which typically indicates damage, from the observed mixture signals.

TL;DR: The feature selection method based on distance evaluation technique is exploited to select the most relevant features and discard the redundant features, and therefore the reliability of the diagnosis performance is further improved.

TL;DR: This paper attempts to summarize the recent development of multiwavelet transform and its applications in mechanical fault diagnosis to construct an image of the contributions of different generation multiwavelets and link the current frontiers with engineering applications for readers interested in this field.

TL;DR: In this article, a cyclostationary method was used to process the vibrations signals acquired from high-speed milling to detect chatter and tool wear in high speed machining.

TL;DR: In this paper, the problem of informative frequency band (IFB) selection in vibration signal processing for local damage detection is discussed and a method based on the local maxima approach is proposed to extend the concept of automatic and objective IFB selection.

TL;DR: In this article, two chatter indicators are developed in the angular domain from the periodic and residual parts of angular speed and cutting force signals, which are used successfully for the detection of the chatter phenomenon.

TL;DR: In this article, a sparse representation based latent component decomposition method is proposed for weak machinery fault detection, which is based on shift-invariant sparse coding algorithm for capturing the underlying structure of machinery fault signal by iteratively solving two convex optimization problems: an L1-regularized least squares problem and an L2-constrained least square problem.

TL;DR: In this paper, a weak signal detection strategy for rolling element bearing fault diagnosis was proposed by investigating a new mechanism to realize stochastic resonance (SR) based on the Woods-Saxon (WS) potential.

TL;DR: The two-step CP–SR damage identification method alleviates the training process required by traditional pattern recognition based methods and can be of small size by formulating the issues of locating damage and assessing damage extent as a two-stage procedure and taking advantage of the robustness of the SR framework.

TL;DR: A critical overview of non-stationary random vibration modelling and analysis via the class of Functional Series Time-dependent AutoRegressive Moving Average (FS-TARMA) models is presented.

TL;DR: In this paper, a dynamic friction model that allows accurate description of friction lag and hysteresis behavior in two regimes, i.e., presliding and sliding regimes, for a tendon sheath in arbitrary configuration such as helical and spatial shape has been developed.

TL;DR: A new transform is proposed, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

TL;DR: In this paper, an efficient and fast subspace-based damage detection test is derived that is robust to changes in the excitation covariance but also to numerical instabilities that can arise easily in the computations.

TL;DR: In this paper, a state-space-based degradation model and associated computational techniques are developed to reduce failure prognostics uncertainty by fusing on-line monitoring data, which is beneficial for risk assessment and optimal maintenance decision-making.

TL;DR: In this article, a mixture Weibull proportional hazard model (MWPHM) is proposed to predict the failure of a mechanical system with multiple failure modes, and the mixed model parameters are estimated by combining historical lifetime and monitoring data of all failure modes.

TL;DR: In this paper, the authors used correlation and wavelet-based analysis for extracting necessary features from the recorded data and used the features obtained from same types of motors with different kind of faults for the classification using the Self-Organizing Maps method.

TL;DR: In this paper, a reference-free fatigue crack detection technique using nonlinear ultrasonic modulation is presented, where the crack-induced spectral sidebands are isolated using a combination of linear response subtraction (LRS), synchronous demodulation (SD) and continuous wavelet transform (CWT) filtering.

TL;DR: These deconvolution methods are applied to cross-spectral imaging function (CSIF) beamforming with auto-spectra exclusion and their properties are demonstrated and compared with each other first by computational simulations consisting of a single source, two incoherent sources and two coherent sources.

TL;DR: In this article, an autonomous algorithm for dynamic displacement estimation from acceleration integration fused with displacement data intermittently measured is presented, which is formulated by unique state definition of integration errors and error dynamics system modeling.

TL;DR: In this paper, the authors presented a fuzzy logic-based robust feedback anti-sway control system which can be applicable either with or without a sensor of sway angle of a payload.

TL;DR: In this paper, an adaptive Kalman filter scheme is proposed for efficient detection as well as tracking of sudden changes in stiffness values, followed by appropriate adjustment of the state covariance matrix for efficient tracking of the states.