Late Oligocene to Middle Miocene rifting and synextensional magmatism in the southwestern Sierra Madre Occidental, Mexico : the beginning of the Gulf of California rift

Although Basin and Range–style extension affected large areas of western Mexico after the Late Eocene, most consider that extension in the Gulf of California region began as subduction waned and ended ca. 14–12.5 Ma. A general consensus also exists in considering Early and Middle Miocene volcanism of the Sierra Madre Occidental and Comondú Group as subduction related, whereas volcanism after ca. 12.5 Ma is extension related. Here we present a new regional geologic study of the eastern Gulf of California margin in the states of Nayarit and Sinaloa, Mexico, backed by 43 new Ar-Ar and U-Pb mineral ages, and geochemical data that document an earlier widespread phase of extension. This extension across the southern and central Gulf Extensional Province began between Late Oligocene and Early Miocene time, but was focused in the region of the future Gulf of California in the Middle Miocene. Late Oligocene to Early Miocene rocks across northern Nayarit and southern Sinaloa were affected by major approximately north-south– to north-northwest– striking normal faults prior to ca. 21 Ma. Between ca. 21 and 11 Ma, a system of north-northwest–south-southeast high angle extensional faults continued extending the southwestern side of the Sierra Madre Occidental. Rhyolitic domes, shallow intrusive bodies, and lesser basalts were emplaced along this extensional belt at 20–17 Ma. Rhyolitic rocks, in particular the domes and lavas, often show strong antecrystic inheritance but only a few Mesozoic or older xenocrysts, suggesting silicic magma generation in the mid-upper crust triggered by an extension induced basaltic infl ux. In northern Sinaloa, large grabens were occupied by huge volcanic dome complexes ca. 21–17 Ma and filled by continental sediments with interlayered basalts dated as 15–14 Ma, a stratigraphy and timing very similar to those found in central Sonora (northeastern Gulf of California margin). Early to Middle Miocene volcanism occurred thus in rift basins, and was likely associated with decompression melting of upper mantle (inducing crustal partial melting) rather than with fluxing by fluids from the young and slow subducting microplates. Along the eastern side of the Gulf of California coast, from Farallón de San Ignacio island offshore Los Mochis, Sinaloa, to San Blas, Nayarit, a strike distance of >700 km, flat lying basaltic lavas dated as ca. 11.5–10 Ma are exposed just above the present sea level. Here crustal thickness is almost half that in the unextended core of the adjacent Sierra Madre Occidental, implying signifi cant lithosphere stretching before ca. 11 Ma. This mafic pulse, with subdued Nb-Ta negative spikes, may be related to the detachment of the lower part of the subducted slab, allowing an upward asthenospheric flow into an upper mantle previously modified by fluid fluxes related to past subduction. Widespread eruption of very uniform oceanic island basalt–like lavas occurred by the late Pliocene and Pleistocene, only 20 m.y. after the onset of rifting and ~9 m.y. after the end of subduction, implying that preexisting subduction-modified mantle had now become isolated from melt source regions. Our study shows that rifting across the southern-central Gulf Extensional Province began much earlier than the Late Miocene and provided a fundamental control on the style and composition of volcanism from at least 30 Ma. We envision a sustained period of lithospheric stretching and magmatism during which the pace and breadth of extension changed ca. 20–18 Ma to be narrower, and again after ca. 12.5 Ma, when the kinematics of rifting became more oblique.

Nonlinear actuator fault detection for small-scale UAS

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

Two-stage power network reconfiguration strategy considering node importance and restored generation capacity

Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.

Fault detection in wind turbine : a systematic literature review

Wind power has become one of the popular renewable resources all over the world and is anticipated to occupy 12% of the total global electricity generation capacity by 2020. For the harsh environment that the wind turbine operates, fault diagnostic and condition monitoring are important for wind turbine safety and reliability. This paper employs a systematic literature review to report the most recent promotions in the wind turbine fault diagnostic, from 2005 to 2012. The frequent faults and failures in wind turbines are considered and different techniques which have been used by researchers are introduced, classified and discussed.

Precedent-free fault isolation in a diesel engine EGR valve system

In this paper, a framework for isolating unprecedented faults for an EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the recently introduced Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for an EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors.

Precedent-free fault isolation in a diesel engine exhaust gas recirculation system

In this paper, a recently introduced model-based method for precedent-free fault detection and isolation (FDI) is modified to deal with multiple input, multiple output (MIMO) systems and is applied to an automotive engine with exhaust gas recirculation (EGR) system. Using normal behavior data generated by a high fidelity engine simulation, the growing structure multiple model system (GSMMS) approach is used to construct dynamic models of normal behavior for the EGR system and its constituent subsystems. Using the GSMMS models as a foundation, anomalous behavior is detected whenever statistically significant departures of the most recent modeling residuals away from the modeling residuals displayed during normal behavior are observed. By reconnecting the anomaly detectors (ADs) to the constituent subsystems, EGR valve, cooler, and valve controller faults are isolated without the need for prior training using data corresponding to particular faulty system behaviors.

Torsional properties of bamboo-like structured Cu nanowires

Recently, researchers reported that nanowires (NWs) are often polycrystalline, which contain grain or twin boundaries that transect the whole NW normal to its axial direction into a bamboo like structure. In this work, large-scale molecular dynamics simulation is employed to investigate the torsional behaviours of bamboo-like structured Cu NWs. The existence of grain boundaries is found to induce a considerably large reduction to the critical angle, and the more of grain boundaries the less reduction appears, whereas, the presence of twin boundaries only results in a relatively smaller reduction to the critical angle. The introduction of grain boundaries reduces the torsional rigidity of the NW, whereas, the twin boundaries exert insignificant influence to the torsional rigidity. NWs with grain boundaries are inclined to produce a local HCP structure during loading, and the plastic deformation is usually evenly distributed along the axial axis of the NW. The plastic deformation of both perfect NW and NWs with twin boundaries is dominated by the nucleation and propagation of parallel intrinsic stacking faults. This study will enrich the current understanding of the mechanical properties of NWs, which will eventually shed lights on their applications.

Tensile properties of Si nanowires with faulted stacking layers

Semiconductor nanowires (NWs) show tremendous applications in micro/nano-electro-mechanical systems. In order to fulfill their promising applications, an understanding of the mechanical properties of NWs becomes increasingly important. Based on the large-scale molecular dynamics simulations, this work investigated the tensile properties of Si NWs with different faulted stacking layers. Different faulted stacking layers were introduced around the centre of the NW by the insertion or removal of certain stacking layers, inducing twins, intrinsic stacking fault, extrinsic stacking fault, and 9R crystal structure. Stress–strain curves obtained from the tensile deformation tests reveal that the presence of faulted stacking layers has induced a considerable decrease to the yield strength while only a minor decrease to Young's modulus. The brittle fracture phenomenon is observed for all tested NWs. In particular, the formation of a monatomic chain is observed for the perfect NW, which exists for a relatively wide strain range. For the defected NW, the monatomic chain appears and lasts shorter. Additionally, all defected NWs show a fracture area near the two ends, in contrast to the perfect NW whose fracture area is adjacent to the middle. This study provides a better understanding of the mechanical properties of Si NWs with the presence of different faulted stacking layers.

Thermal conductivity of Si nanowires with faulted stacking layers

Faulted stacking layers are ubiquitously observed during the crystal growth of semiconducting nanowires (NWs). In this paper, we employ the reverse non-equilibrium molecular dynamics simulation to elucidate the effect of various faulted stacking layers on the thermal conductivity (TC) of silicon (Si) NWs. We find that the stacking faults can greatly reduce the TC of the Si NW. Among the different stacking faults that are parallel to the NW's axis, the 9R polytype structure, the intrinsic and extrinsic stacking faults (iSFs and eSFs) exert more pronounced effects in the reduction of TC than the twin boundary (TB). However, for the perpendicularly aligned faulted stacking layers, the eSFs and 9R polytype structures are observed to induce a larger reduction to the TC of the NW than the TB and iSFs. For all considered NWs, the TC does not show a strong relation with the increasing number of faulted stacking layers. Our studies suggest the possibility of tuning the thermal properties of Si NWs by altering the crystal structure via the different faulted stacking layers.

The relationship between kurtosis- and envelope-based indexes for the diagnostic of rolling element bearings

The coupling of kurtosis based-indexes and envelope analysis represents one of the most successful and widespread procedures for the diagnostics of incipient faults on rolling element bearings. Kurtosis-based indexes are often used to select the proper demodulation band for the application of envelope-based techniques. Kurtosis itself, in slightly different formulations, is applied for the prognostic and condition monitoring of rolling element bearings, as a standalone tool for a fast indication of the development of faults. This paper shows for the first time the strong analytical connection which holds for these two families of indexes. In particular, analytical identities are shown for the squared envelope spectrum (SES) and the kurtosis of the corresponding band-pass filtered analytic signal. In particular, it is demonstrated how the sum of the peaks in the SES corresponds to the raw 4th order moment. The analytical results show as well a link with an another signal processing technique: the cepstrum pre-whitening, recently used in bearing diagnostics. The analytical results are the basis for the discussion on an optimal indicator for the choice of the demodulation band, the ratio of cyclic content (RCC), which endows the kurtosis with selectivity in the cyclic frequency domain and whose performance is compared with more traditional kurtosis-based indicators such as the protrugram. A benchmark, performed on numerical simulations and experimental data coming from two different test-rigs, proves the superior effectiveness of such an indicator. Finally a short introduction to the potential offered by the newly proposed index in the field of prognostics is given in an additional experimental example. In particular the RCC is tested on experimental data collected on an endurance bearing test-rig, showing its ability to follow the development of the damage with a single numerical index.

Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals

Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Enhanced locomotion control for a planetary rover

This article presents an approach to improve and monitor the behavior of a skid-steering rover on rough terrains. An adaptive locomotion control generates speeds references to avoid slipping situations. An enhanced odometry provides a better estimation of the distance travelled. A probabilistic classification procedure provides an evaluation of the locomotion efficiency on-line, with a detection of locomotion faults. Results obtained with a Marsokhod rover are presented throughout the paper

HeatWave : a handheld 3D thermography system for energy auditing

Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.