The study investigates textural characteristics of sediment at selected tourist beaches extending from Rameswaram to Paradip along east coast of India. Samples were taken from backshore and foreshore at nine selected locations to evaluate sediment grain size distribution and its seasonality. Analysis of grain size distribution carried out to identify textural characteristics (mean size, standard deviation, skewness and kurtosis) and its variability in two different seasons (southwest and northeast monsoon). Results show that sediments lying in backshore regions are mostly medium sand, while its changes are relatively invariant against seasons. The percentage of fine sand is higher during January compared to September due to prevalence of calm wave conditions. The mean grain size trend decreases at backshore region while it increases at foreshore region from south to north along the coast indicating dominance of aeolian transport. Sediments are mostly moderately sorted at backshore and moderately well sorted at foreshore region. Mostly symmetrical and mesokurtic sediments are dominated along the coast indicating sediments are well sorted at central portion of sediment distribution. The CM diagram depicts sediment source are from beach environment during both the seasons and some of them transported by tractive current in September and transporting during September is by rolling, bottom suspension and rolling; and graded suspension no rolling.
Early fault identification of the rolling element bearings remains difficult because the repetitive transient signature generated via localized incipient damage is easily submerged by various interference components and strong noise. Spectral coherence (SCoh) is a break- through approach for revealing the second-order cyclostationary of bearing faults by displaying the energy flow of vibration signal jointly in a two-dimensional plane comprising the resonance frequency and bearing fault frequency. Considering the non-uniformity of fault in- formation distribution in the whole spectral frequency band, the enhanced envelope spectrum (EES) obtained by integrating over the full spectral frequency band is vulnerable to strong background noise. Thus, how to identify an informative spectral frequency band for constructing a diagnostic improved envelope spectrum (IES) is crucial to accurately identify bearing faults. To address this issue, a feature- adaptive method called IES via Candidate Fault Frequency Optimization-gram (IESCFFOgram) is proposed to determine the in- formative spectral frequency band from SCoh for bearing fault diagnosis. The innovation of this method is to fully excavate the fault information hidden in the SCoh and adaptively determine the informative spectral frequency band according to the identified candidate fault frequencies. The proposed method is tested and validated on simulated signals, vibration datasets obtained from artificial fault bearing experiments, and accelerated bearing degradation tests. In addition, comparisons with state-of-the art methods have been conducted to highlight the superiority of the proposed methodology.
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