Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.     

On the detection of anomalous seismo-ionospheric behavior in the presence of space weather stimuli for large earthquakes

Anomalous behavior of ionospheric total electron content (TEC) prior to earthquake has been observed in many studies. Evidence of such seismo-ionospheric coupling effects suggests that it is plausible to rely on TEC signatures for early earthquake warning. However, the detection of pre-earthquake TEC anomalies (PETA) has not been adopted in practice due to two pertinent issues. Firstly, the effects of space weather activity can affect TEC levels and cause anomalous behavior in the TEC. Usually arbitrary thresholds are set for space weather indices to eliminate TEC anomaly due to space weather effects. Secondly, the choice regarding moving time-window length used to characterise background variation of TEC within the statistical envelope approach has an effect on detection of PETA. While the rule-of-thumb in selecting the moving window length is to have a time window capable of capturing background variability and short-term fluctuations, the length of the time window used in the literature varies with little justification. In this study, a critical examination is conducted on the statistical envelope approach and in particular, to eliminate the effect of space weather activity without the use of arbitrary space indices to detect PETA. A two-part PETA identification procedure is proposed, consisting of wavelet analyses isolating non-earthquake TEC contributions, followed by the statistical envelope method using a moving window length standardized based on observed periodicities and statistical implications is suggested. The approach is tested on a database of 30 large earthquakes (M?≥?7.0). The proposed procedure shows that PETA can be detected prior to earthquakes at higher confidence levels without the need to separately check for space weather activity. More importantly, the procedure was able to detect PETA for studies where it was previously reported that PETA could not be detected or detected convincingly.     

Variation of hmF2 and NmF2 deduced from DPS-4 over Multan (Pakistan) and their comparisons with IRI-2012 & IRI-2016 during the deep solar minimum between cycles 23 & 24

We report the results of ionospheric measurements from DPS-4 installed at Multan (Geog coord. 30.18°N, 71.48°E, dip 47.4°). The variations in F2-layer maximum electron density NmF2 and its peak height hmF2 are studied during the deep solar minimum between cycles 23 & 24 i.e 2008–2009 with comparisons conducted with the International Reference Ionosphere (IRI) versions 2012 & 2016. We find that the hmF2 observations peak around the pre-sunrise and sunrise hours depending on the month. Seasonally, the daytime variation of NmF2 is higher in the Equinox and Summer, while daytime hmF2 are slightly higher in the Equinox and Winter. High values of hmF2 around midnight are caused by an increase of upward drifts produced by meridional winds. The ionosphere over Multan, which lies at the verge of low and mid latitude, is affected by both $E\times B$ drifts and thermospheric winds as evident from mid-night peaks and near-sunrise dips in hmF2. The results of the comparison of the observed NmF2 and hmF2 for the year 2008–2009 with the IRI-2012 (both NmF2 and hmF2) and IRI-2016 (only hmF2) estimates indicate that for NmF2, IRI-2012 with Consultative Committee International Radio (CCIR) option produces values in better agreement with observed data. Whereas, for hmF2, IRI-2016 with both International Union of Radio Science (URSI) and CCIR SHU-2015 options, predicts well for nighttime hours throughout the year. However, the IRI-2012 with CCIR option produces better agreement with data during daytime hours. Furthermore, IRI-2012 with CCIR option gives better results during Equinox months, whereas, IRI-2016 with both URSI and CCIR SHU-2015 options predict well for Winter and Summer.     

Flutter analysis of hybrid metal-composite low aspect ratio trapezoidal wings in supersonic flow

An effective 3D supersonic Mach box approach in combination with non-classical hybrid metal-composite plate theory has been used to investigate flutter boundaries of trapezoidal low aspect ratio wings. The wing structure is composed of two main components including alu-minum material (in-board section) and laminated composite material (out-board section). A global Ritz method is used with simple polynomials being employed as the trial functions. The most important objective of the present research is to study the effect of composite to metal proportion of hybrid wing structure on flutter boundaries in low supersonic regime. In addition, the effect of some important geometrical parameters such as sweep angle, taper ratio and aspect ratio on flutter boundaries were studied. The results obtained by present approach for special cases like pure metal-lic wings and results for high supersonic regime based on piston theory show a good agreement with those obtained by other investigators.     

Monitoring spatio-temporal variations in aerosols and aerosol–cloud interactions over Pakistan using MODIS data

Clouds are important elements in climatic processes and interactions between aerosols and clouds are therefore a hot topic for scientific research. Aerosols show both spatial and temporal variations, which can lead to variations in the microphysics of clouds. In this research, we have examined the spatial and temporal variations in aerosol particles over Pakistan and the impact of these variations on various optical properties of clouds, using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra satellite. We used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for trajectory analysis to reveal the origins of air masses, with the aim of understanding these spatial and temporal variabilities in aerosol concentrations. We also documented seasonal variations in patterns of aerosol optical depth (AOD) over Pakistan, for which the highest values occur during the monsoon season (June–August). We then analyzed the relationships between AOD and four other cloud parameters, namely water vapour (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP). Regional correlation maps and time series plots for aerosol (AOD) and cloud parameters were produced to provide a better understanding of aerosol–cloud interaction. The analyses showed strong positive correlations between AOD and WV for all of the eight cities investigated. The correlation between AOD and CF was positive for those cities where the air masses were predominantly humid, but negative for those cities where the air masses were relatively dry and carried a low aerosol abundance. These correlations were clearly dependent on the meteorological conditions for all of the eight cities investigated. Because of the observed AOD–CF relationship, the co-variation of AOD with CTP and CTT may be attributable to large-scale meteorological variations: AOD showed a positive correlation with CTP and CTT in northern regions of Pakistan and a negative correlation in southern regions.     

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators. The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID (FOPID) controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead (N-M) optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers.