Analysis of multi-degree-of-freedom nonlinear systems using nonlinear output frequency response functions

The analysis of multi-degree-of-freedom (MDOF) nonlinear systems is studied using the concept of Nonlinear Output Frequency Response Functions (NOFRFs). The results reveal very important properties of MDOF systems, which are of significant importance for the analysis of nonlinear structures. One important application of the results obtained in this study is the detection and location of faults in engineering structures which make the structures behave nonlinearly

Automatic Reconstruction of Fault Networks from Seismicity Catalogs: 3D Optimal Anisotropic Dynamic Clustering

We propose a new pattern recognition method that is able to reconstruct the 3D structure of the active part of a fault network using the spatial location of earthquakes. The method is a generalization of the so-called dynamic clustering method, that originally partitions a set of datapoints into clusters, using a global minimization criterion over the spatial inertia of those clusters. The new method improves on it by taking into account the full spatial inertia tensor of each cluster, in order to partition the dataset into fault-like, anisotropic clusters. Given a catalog of seismic events, the output is the optimal set of plane segments that fits the spatial structure of the data. Each plane segment is fully characterized by its location, size and orientation. The main tunable parameter is the accuracy of the earthquake localizations, which fixes the resolution, i.e. the residual variance of the fit. The resolution determines the number of fault segments needed to describe the earthquake catalog, the better the resolution, the finer the structure of the reconstructed fault segments. The algorithm reconstructs successfully the fault segments of synthetic earthquake catalogs. Applied to the real catalog constituted of a subset of the aftershocks sequence of the 28th June 1992 Landers earthquake in Southern California, the reconstructed plane segments fully agree with faults already known on geological maps, or with blind faults that appear quite obvious on longer-term catalogs. Future improvements of the method are discussed, as well as its potential use in the multi-scale study of the inner structure of fault zones

Desıgn of a control and data acquısıtıon system for a multı-mode solar trackıng farm

This paper presents a combination network design for a solar tracking farm consisting of n-solar tracking systems. Serial communication protocol has been adopted for this network with developed strategy to make the farm expandable for possible future extension. The master control unit is responsible for managing all the trackers of the sun location in multi-tracking mode, diagnosis all the trackers for any faults and give complete information about the produced power by each of the solar tracking system. This network protocols is designed to deal with the error control, congestion control and flow control for data transmission in the network

Improved transient simulation of salient-pole synchronous generators with internal and ground faults in the stator winding

An improved model for simulating the transient behavior of salient-pole synchronous generators with internal and ground faults in the stator winding is established using the multi-loop circuit method. The model caters for faults under different ground conditions for the neutral, and accounts for the distributed capacitances of the windings to ground. Predictions from the model are validated by experiments, and it is shown that the model accurately predicts the voltage and current waveforms under fault conditions. Hence, it can be used to analyze important features of faults and to design appropriate protection schemes

Hierarchical strategies for efficient fault recovery on the reconfigurable PAnDA device

A novel hierarchical fault-tolerance methodology for reconfigurable devices is presented. A bespoke multi-reconfigurable FPGA architecture, the programmable analogue and digital array (PAnDA), is introduced allowing fine-grained reconfiguration beyond any other FPGA architecture currently in existence. Fault blind circuit repair strategies, which require no specific information of the nature or location of faults, are developed, exploiting architectural features of PAnDA. Two fault recovery techniques, stochastic and deterministic strategies, are proposed and results of each, as well as a comparison of the two, are presented. Both approaches are based on creating algorithms performing fine-grained hierarchical partial reconfiguration on faulty circuits in order to repair them. While the stochastic approach provides insights into feasibility of the method, the deterministic approach aims to generate optimal repair strategies for generic faults induced into a specific circuit. It is shown that both techniques successfully repair the benchmark circuits used after random faults are induced in random circuit locations, and the deterministic strategies are shown to operate efficiently and effectively after optimisation for a specific use case. The methods are shown to be generally applicable to any circuit on PAnDA, and to be straightforwardly customisable for any FPGA fabric providing some regularity and symmetry in its structure

Segmentation of Fault Networks Determined from Spatial Clustering of Earthquakes

We present a new method of data clustering applied to earthquake catalogs, with the goal of reconstructing the seismically active part of fault networks. We first use an original method to separate clustered events from uncorrelated seismicity using the distribution of volumes of tetrahedra defined by closest neighbor events in the original and randomized seismic catalogs. The spatial disorder of the complex geometry of fault networks is then taken into account by defining faults as probabilistic anisotropic kernels, whose structures are motivated by properties of discontinuous tectonic deformation and previous empirical observations of the geometry of faults and of earthquake clusters at many spatial and temporal scales. Combining this a priori knowledge with information theoretical arguments, we propose the Gaussian mixture approach implemented in an Expectation-Maximization (EM) procedure. A cross-validation scheme is then used and allows the determination of the number of kernels that should be used to provide an optimal data clustering of the catalog. This three-steps approach is applied to a high quality relocated catalog of the seismicity following the 1986 Mount Lewis ($M_l=5.7$) event in California and reveals that events cluster along planar patches of about 2 km$^2$, i.e. comparable to the size of the main event. The finite thickness of those clusters (about 290 m) suggests that events do not occur on well-defined euclidean fault core surfaces, but rather that the damage zone surrounding faults may be seismically active at depth. Finally, we propose a connection between our methodology and multi-scale spatial analysis, based on the derivation of spatial fractal dimension of about 1.8 for the set of hypocenters in the Mnt Lewis area, consistent with recent observations on relocated catalogs

Cooperative Virtual Sensor for Fault Detection and Identification in Multi-UAV Applications

This paper considers the problem of fault detection and identification (FDI) in applications carried out by a group of unmanned aerial vehicles (UAVs) with visual cameras. In many cases, the UAVs have cameras mounted onboard for other applications, and these cameras can be used as bearing-only sensors to estimate the relative orientation of another UAV. The idea is to exploit the redundant information provided by these sensors onboard each of the UAVs to increase safety and reliability, detecting faults on UAV internal sensors that cannot be detected by the UAVs themselves. Fault detection is based on the generation of residuals which compare the expected position of a UAV, considered as target, with the measurements taken by one or more UAVs acting as observers that are tracking the target UAV with their cameras. Depending on the available number of observers and the way they are used, a set of strategies and policies for fault detection are defined. When the target UAV is being visually tracked by two or more observers, it is possible to obtain an estimation of its 3D position that could replace damaged sensors. Accuracy and reliability of this vision-based cooperative virtual sensor (CVS) have been evaluated experimentally in a multivehicle indoor testbed with quadrotors, injecting faults on data to validate the proposed fault detection methods.Comisión Europea H2020 644271Comisión Europea FP7 288082Ministerio de Economia, Industria y Competitividad DPI2015-71524-RMinisterio de Economia, Industria y Competitividad DPI2014-5983-C2-1-RMinisterio de Educación, Cultura y Deporte FP

Agent Based Test and Repair of Distributed Systems

This article demonstrates how to use intelligent agents for testing and repairing a distributed system, whose elements may or may not have embedded BIST (Built-In Self-Test) and BISR (Built-In Self-Repair) facilities. Agents are software modules that perform monitoring, diagnosis and repair of the faults. They form together a society whose members communicate, set goals and solve tasks. An experimental solution is presented, and future developments of the proposed approach are explore