A novel traveling-wave-based method improved by unsupervised learning for fault location of power cables via sheath current monitoring

In order to improve the practice in maintenance of power cables, this paper proposes a novel traveling-wave-based fault location method improved by unsupervised learning. The improvement mainly lies in the identification of the arrival time of the traveling wave. The proposed approach consists of four steps: (1) The traveling wave associated with the sheath currents of the cables are grouped in a matrix; (2) the use of dimensionality reduction by t-SNE (t-distributed Stochastic Neighbor Embedding) to reconstruct the matrix features in a low dimension; (3) application of the DBSCAN (density-based spatial clustering of applications with noise) clustering to cluster the sample points by the closeness of the sample distribution; (4) the arrival time of the traveling wave can be identified by searching for the maximum slope point of the non-noise cluster with the fewest samples. Simulations and calculations have been carried out for both HV (high voltage) and MV (medium voltage) cables. Results indicate that the arrival time of the traveling wave can be identified for both HV cables and MV cables with/without noise, and the method is suitable with few random time errors of the recorded data. A lab-based experiment was carried out to validate the proposed method and helped to prove the effectiveness of the clustering and the fault location

Support Vector Regression Based S-transform for Prediction of Single and Multiple Power Quality Disturbances

This paper presents a novel approach using Support Vector Regression (SVR) based S-transform to predict the classes of single and multiple power quality disturbances in a three-phase industrial power system. Most of the power quality disturbances recorded in an industrial power system are non-stationary and comprise of multiple power quality disturbances that coexist together for only a short duration in time due to the contribution of the network impedances and types of customers’ connected loads. The ability to detect and predict all the types of power quality disturbances encrypted in a voltage signal is vital in the analyses on the causes of the power quality disturbances and in the identification of incipient fault in the networks. In this paper, the performances of two types of SVR based S-transform, the non-linear radial basis function (RBF) SVR based S-transform and the multilayer perceptron (MLP) SVR based S-transform, were compared for their abilities in making prediction for the classes of single and multiple power quality disturbances. The results for the analyses of 651 numbers of single and multiple voltage disturbances gave prediction accuracies of 86.1% (MLP SVR) and 93.9% (RBF SVR) respectively. Keywords: Power Quality, Power Quality Prediction, S-transform, SVM, SV

Minimizing the residual topography effect on interferograms to improve DInSAR results: estimating land subsidence in Port-Said City, Egypt

The accurate detection of land subsidence rates in urban areas is important to identify damage-prone areas and provide decision-makers with useful information. Meanwhile, no precise measurements of land subsidence have been undertaken within the coastal Port-Said City in Egypt to evaluate its hazard in relationship to sea-level rise. In order to address this shortcoming, this work introduces and evaluates a methodology that substantially improves small subsidence rate estimations in an urban setting. Eight ALOS/PALSAR-1 scenes were used to estimate the land subsidence rates in Port-Said City, using the Small BAse line Subset (SBAS) DInSAR technique. A stereo pair of ALOS/PRISM was used to generate an accurate DEM to minimize the residual topography effect on the generated interferograms. A total of 347 well distributed ground control points (GCP) were collected in Port-Said City using the leveling instrument to calibrate the generated DEM. Moreover, the eight PALSAR scenes were co-registered using 50 well-distributed GCPs and used to generate 22 interferogram pairs. These PALSAR interferograms were subsequently filtered and used together with the coherence data to calculate the phase unwrapping. The phase-unwrapped interferogram-pairs were then evaluated to discard four interferograms that were affected by phase jumps and phase ramps. Results confirmed that using an accurate DEM (ALOS/PRISM) was essential for accurately detecting small deformations. The vertical displacement rate during the investigated period (2007–2010) was estimated to be −28 mm. The results further indicate that the northern area of Port-Said City has been subjected to higher land subsidence rates compared to the southern area. Such land subsidence rates might induce significant environmental changes with respect to sea-level rise

Mapping constrained optimization problems to quantum annealing with application to fault diagnosis

Current quantum annealing (QA) hardware suffers from practical limitations such as finite temperature, sparse connectivity, small qubit numbers, and control error. We propose new algorithms for mapping boolean constraint satisfaction problems (CSPs) onto QA hardware mitigating these limitations. In particular we develop a new embedding algorithm for mapping a CSP onto a hardware Ising model with a fixed sparse set of interactions, and propose two new decomposition algorithms for solving problems too large to map directly into hardware. The mapping technique is locally-structured, as hardware compatible Ising models are generated for each problem constraint, and variables appearing in different constraints are chained together using ferromagnetic couplings. In contrast, global embedding techniques generate a hardware independent Ising model for all the constraints, and then use a minor-embedding algorithm to generate a hardware compatible Ising model. We give an example of a class of CSPs for which the scaling performance of D-Wave's QA hardware using the local mapping technique is significantly better than global embedding. We validate the approach by applying D-Wave's hardware to circuit-based fault-diagnosis. For circuits that embed directly, we find that the hardware is typically able to find all solutions from a min-fault diagnosis set of size N using 1000N samples, using an annealing rate that is 25 times faster than a leading SAT-based sampling method. Further, we apply decomposition algorithms to find min-cardinality faults for circuits that are up to 5 times larger than can be solved directly on current hardware.Comment: 22 pages, 4 figure

The 2010 MW 6.8 Yushu (Qinghai, China) earthquake: constraints provided by InSAR and body wave seismology

By combining observations from satellite radar, body wave seismology and optical imagery, we have determined the fault segmentation and sequence of ruptures for the 2010 Mw 6.8 Yushu (China) earthquake. We have mapped the fault trace using displacements from SAR image matching, interferometric phase and coherence, and 2.5 m SPOT-5 satellite images. Modeling the event as an elastic dislocation with three segments fitted to the fault trace suggests that the southeast and northwest segments are near vertical, with the central segment dipping 70° to the southwest; slip occurs mainly in the upper 10 km, with a maximum slip of 1.5 m at a depth of 4 km on the southeastern segment. The maximum slip in the top 1 km (i.e., near surface) is up to 1.2 m, and inferred locations of significant surface rupture are consistent with displacements from SAR image matching and field observations. The radar interferograms show rupture over a distance of almost 80 km, much larger than initial seismological and field estimates of the length of the fault. Part of this difference can be attributed to slip on the northwestern segment of the fault being due to an Mw 6.1 aftershock two hours after the main event. The remaining difference can be explained by a non-uniform slip distribution with much of the moment release occurring at depths of less than 10 km. The rupture on the central and southeastern segments of the fault in the main shock propagated at a speed of 2.5 km/s southeastward toward the town of Yushu located at the end of this segment, accounting for the considerable building damage. Strain accumulation since the last earthquake on the fault segment beyond Yushu is equivalent to an Mw 6.5 earthquake