Showing papers in "Mechanical Systems and Signal Processing in 2013"

TL;DR: This paper attempts to survey and summarize the recent research and development of EMD in fault diagnosis of rotating machinery, providing comprehensive references for researchers concerning with this topic and helping them identify further research topics.

TL;DR: A systematic review of over 20 major time-frequency analysis methods reported in more than 100 representative articles published since 1990 can be found in this article, where their fundamental principles, advantages and disadvantages, and applications to fault diagnosis of machinery have been examined.

TL;DR: Evidence theory, probability bounds analysis with p-boxes, and fuzzy probabilities are discussed with emphasis on their key features and on their relationships to one another.

TL;DR: In this paper, a Wiener-process-based degradation model with a recursive filter algorithm is developed to estimate the remaining useful life estimation (RUL) from the observed degradation data.

TL;DR: In this paper, the authors proposed an enhanced Kurtogram based on the power spectrum of the envelope of the signals extracted from wavelet packet nodes at different depths, which measured the protrusion of the sparse representation.

TL;DR: In this paper, an extensive monitoring campaign of the Tamar Suspension Bridge as well as analysis carried out in an attempt to understand the bridge's normal condition are investigated. And the initial steps towards the development of a structural health monitoring system for the TAMAR Bridge are addressed.

TL;DR: In this paper, an adaptive stochastic resonance (ASR) method was proposed for fault diagnosis of planetary gearboxes, which utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastically resonance system matching input signals.

TL;DR: The results show that the proposed method outperforms other methods both mentioned in this paper and published in other literatures.

TL;DR: In this paper, a novel method called improved EEMD with multi-wavelet packet for rotating machinery multi-fault diagnosis is proposed, which uses multiwavelet packets as the pre-filter to improve the decomposition results.

TL;DR: In this paper, a simple time series method for bearing fault feature extraction using singular spectrum analysis (SSA) of the vibration signal is proposed, which is easy to implement and fault feature is noise immune.

TL;DR: In this paper, the sparsogram is constructed using the sparsity measurements of the power spectra from the envelopes of wavelet packet coefficients at different wavelet decomposition depths.

TL;DR: In this article, an active interface condition monitoring approach for concrete-filled steel tube (CFST) by the use of lead zirconate titanate (PZT) piezoceramics based functional smart aggregates (SAs) embedded in concrete as actuator and PZT patches bonded on the surface of the steel tube as sensors is proposed and verified experimentally.

TL;DR: In this paper, a sparsity-enabled signal decomposition method was proposed to extract fault features of gearboxes by analyzing the oscillatory behavior of the signal rather than the frequency or scale.

TL;DR: In this article, a large-scale literature review of rotor-stator contacts with stators is presented, highlighting the phenomenology involved in different rotor to stator contacts configurations and confirming the great complexity of the problems which involve multiphysics and multiscale coupled behaviors.

TL;DR: In this article, a new technique for pre-whitening has been proposed, based on cepstral analysis, which seems a good candidate to perform the intermediate pre-whiteening step in an automatic damage recognition algorithm.

TL;DR: The use of optical backscatter reflectometer (OBR) sensors is a promising measurement technology for Structural Health Monitoring (SHM) as it offers the possibility of continuous monitoring of strain and temperature along the fiber.

TL;DR: In this article, the authors applied the approximate entropy (ApEn) method and empirical mode decomposition (EMD) to clearly separate the entry-exit events, and thus the size of the spall-like fault is estimated.

TL;DR: A new two-step method for instantaneous frequency estimation based on principles of phase demodulation and joint time-frequency analysis, taking advantage of both of them is proposed.

TL;DR: In this article, the authors proposed an interval quasi-Monte Carlo simulation methodology to efficiently compute the bounds of structure failure probability, which is based on deterministic lowdiscrepancy sequences, which are distributed more regularly than the (pseudo) random points in direct Monte Carlo simulation.

TL;DR: This work presents a novel classification technique designed for real-time applications inspired by the sequential k-means procedure, i.e., both the number of clusters and their elements are inferred from the data distribution in a multi-dimensional metric space.

TL;DR: In this article, a tacho-less order tracking method is established for any speed variations including large speed variation such as run-up or run-down process of machinery, where a Chirplet-based approach is proposed to estimate the instantaneous frequency of a certain harmonic of rotating frequency.

TL;DR: In this article, an integrated anomaly detection approach for seeded bearing faults is presented, in which the Empirical Mode Decomposition and the Hilbert Huang transform are employed for the extraction of a compact feature set.

TL;DR: In this paper, a torsional vibration signal analysis of planetary gearboxes is proposed to diagnose a single gear fault of a planetary gearbox, which can also be generalized to detect and locate multiple gear faults.

TL;DR: In this paper, a critical review of the state-of-the-art highlighting the major difficulties when using transmissibility functions for damage detection and localization is presented, and an analytical study is presented for non dispersive systems such as chain-like mass-spring systems.

TL;DR: Based on the operating deflection shape curvature and the assumption that the intact structure is smooth and homogenous, a new damage detection algorithm called Global Filtering Method (GFM) is proposed in this paper.

TL;DR: In this paper, a novel method for fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis (MF-DFA) and Mahalanobis distance criterion (MDC) was proposed.

TL;DR: In this article, a wavelet transform is applied to the difference of the mode shape vectors to obtain information of the changes in each of them and the results for each mode are added up to compute an overall result along the structure.

TL;DR: The results show that the proposed diagnosis system is capable of improving the classification accuracy and efficiently assisting in rotating machinery fault diagnosis.

TL;DR: In this article, an adaptive wavelet threshold (AWT) de-noising, ensemble empirical mode decomposition (EEMD) and correlation dimension (CD) is used for diesel engine faults.