One-pass Scan Research Articles

New design of rotating eddy current probe for arbitrary orientation cracks detection

PurposeDetecting the orientation of cracks is a major challenge in the development of eddy current nondestructive testing probes. Eddy current-based techniques are limited in their ability to detect cracks that are not perpendicular to induced current flows. This study aims to investigate the application of the rotating electromagnetic field method to detect arbitrary orientation defects in conductive nonferrous parts. This method significantly improves the detection of cracks of any orientation.Design/methodology/approachA new rotating uniform eddy current (RUEC) probe is presented. Two exciting pairs consisting of similar square-shaped coils are arranged orthogonally at the same lifting point, thus avoiding further adjustment of the excitation system to generate a rotating electromagnetic field, eliminating any need for mechanical rotation and focusing this field with high density. A circular detection coil serving as a receiver is mounted in the middle of the excitation system.FindingsA simulation model of the rotating electromagnetic field system is performed to determine the rules and characteristics of the electromagnetic signal distribution in the defect area. Referring to the experimental results aimed to detect artificial cracks at arbitrary angles in underwater structures using the rotating alternating current field measurement (RACFM) system in Li et al. (2016), the model proposed in this paper is validated.Originality/valueCEDRAT FLUX 3D simulation results showed that the proposed probe can detect cracks with any orientation, maintaining the same sensitivity, which demonstrates its effectiveness. Furthermore, the proposed RUEC probe, associated with the exploitation procedure, allows us to provide a full characterization of the crack, namely, its length, depth and orientation in a one-pass scan, by analyzing the magnetic induction signal.

Approximating median absolute deviation with bounded error

The median absolute deviation (MAD) is a statistic measuring the variability of a set of quantitative elements. It is known to be more robust to outliers than the standard deviation (SD), and thereby widely used in outlier detection. Computing the exact MAD however is costly, e.g., by calling an algorithm of finding median twice, with space cost O ( n ) over n elements in a set. In this paper, we propose the first fully mergeable approximate MAD algorithm, OP-MAD, with one-pass scan of the data. Remarkably, by calling the proposed algorithm at most twice, namely TP-MAD, it guarantees to return an (ϵ, 1)-accurate MAD, i.e., the error relative to the exact MAD is bounded by the desired ϵ or 1. The space complexity is reduced to O ( m ) while the time complexity is O ( n + m log m ), where m is the size of the sketch used to compress data, related to the desired error bound ϵ. To get a more accurate MAD, i.e., with smaller ϵ, the sketch size m will be larger, a trade-off between effectiveness and efficiency. In practice, we often have the sketch size m ≪ n , leading to constant space cost O (1) and linear time cost O ( n ). The extensive experiments over various datasets demonstrate the superiority of our solution, e.g., 160000× less memory and 18x faster than the aforesaid exact method in datasets pareto and norm . Finally, we further implement and evaluate the parallelizable TP-MAD in Apache Spark, and the fully mergeable OP-MAD in Structured Streaming.

One-Pass Inconsistency Detection Algorithms for Big Data

Data in the real world is often dirty. Inconsistency is an important kind of dirty data; before repairing inconsistency, we need to detect them first. The time complexities of the current inconsistency detection algorithms are super-linear to the size of data and not suitable for the big data. For the inconsistency detection of big data, we develop an algorithm that detects inconsistency within the one-pass scan of the data according to both the functional dependency (FD) and the conditional functional dependency (CFD) in our previous work. In this paper, we propose inconsistency detection algorithms in terms of FD, CFD, and Denial Constraint (DC). DCs are more expressive than FDs and CFDs. Developing the algorithm to detect the violation of DCs increases the applicability of our inconsistency detection algorithms. We compare the performance of our algorithm with the performance of implementing SQL queries in MySQL and BigQuery. The experimental results indicate the high efficiency of our algorithms.

Inner circumferential current field testing system with TMR sensor arrays for inner-wall cracks inspection in aluminum tubes

Detection, localization and evaluation of internal defects are important subjects for the integrity management of aluminum tubes which are widely used in heat exchange, aerospace, transport and construction fields. Conventional nondestructive testing (NDT) methods are difficult to detect, locate and evaluate the internal defect in aluminum tubes in a one-pass scan. This paper presents an inner circumferential current field testing method for the inspection of inner-wall longitudinal cracks in aluminum tubes. The theory of the inner circumferential current field testing method is proposed, which is verified by simulations and experiments. The inner circumferential current field testing system is developed with tunnel magneto resistance (TMR) sensor arrays and the inner-wall longitudinal crack detection experiments are carried out in an aluminum tube. The results show that the inner-wall longitudinal crack can be detected, positioned and evaluated inside the aluminum tube in a one-pass scan using the circumferential current field testing system with TMR sensor arrays.

Controlling of residual stress in additive manufacturing of Ti6Al4V by finite element modeling

Minimizing the residual stress build-up in metal-based additive manufacturing plays a pivotal role in selecting a particular material and technique for making an industrial part. In beam-based additive manufacturing, although a great deal of effort has been made to minimize the residual stresses, it is still elusive how to do so by simply optimizing the manufacturing parameters, such as beam size, beam power, and scan speed. With reference to the Ti6Al4V alloy and manufacturing by electron beam melting, we perform systematic finite element modeling of one-pass scanning to study the effects of beam size, beam power density, beam scan speed, and chamber bed temperature on the magnitude and distribution of residual stresses. Our study elucidates both qualitative and quantitative features of the residual stress fields originated by these manufacturing parameters. Our findings can serve as useful guidelines for engineers and designers to deal with residual stress build-up during additive manufacturing of Ti6Al4V.

CVS: Fast cardinality estimation for large-scale data streams over sliding windows

Estimating the cardinality of data streams over a sliding window is an important problem in many applications, such as network traffic monitoring, web access log analysis and database. The problem becomes more difficult in large-scale data streams when time and space complexity is taken into account. In this paper, we present a novel randomized data structure to address the problem. The significant contributions are as follows: (1) A space-efficient counter vector sketch (CVS) are proposed, which extends the well-known bitmap sketch to sliding window settings. (2) Based on the CVS, a random update mechanism is introduced, whereby a small fixed number of entries are randomly chosen from CVS in a step and then updated. This means that the update procedure just costs constant time. (3) Furthermore, estimating cardinality by CVS just needs one-pass scan of the data. (4) Finally, a theoretical analysis is given to show the accuracy of CVS-based estimators. Our comprehensive experiments confirm that the CVS-based schema attains high accuracy, and demonstate its time efficiency in comparison with the Timestamp Vector (TSV) and the auxiliary indexing method.

One-pass Moment Algorithm for Graphical Primitives

Moment is a useful tool in character and drawing recognition. As the moment computation is time-consuming, the main aim in this area is to develop a fast algorithm. The commonly-used method is the discrete Green’s theorem, which transforms the double summation into a summation on region contour. An improved discrete Green’s theorem proposed in this paper, which removes the constraint on parity pairing, thus extends its validity in applying the algorithm to complex regions. The contour tracing is fulfilled by a boundary-tracing-automation, and the central moments for graphical primitives are computed by one-pass scanning algorithm, the calculation of the moment is greatly simplified DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.5099

A Cascade Framework for a Real-Time Statistical Plate Recognition System

This paper describes a plate recognition system that can process images rapidly at high accuracy rates. This system is designed to meet the requirements of performance, computational speed, and adaptation for vehicle surveillance applications, such as stolen car detection systems. These requirements are satisfied by adopting a cascade framework, utilizing plate characteristics, and developing fast one-pass algorithms. Our system is composed of three main cascading modules for plate detection, character segmentation, and postprocessing. Each module is further decomposed into several cascading procedures, which are composed of successively more complex rejecters. The first module rapidly rejects a majority of nonplate regions by using low computational gradient features and a one-pass scanning algorithm followed by heavy computational statistical rejecters. The second module rejects a majority of noncharacter regions in a similar manner. A peak-valley analysis algorithm is proposed to rapidly detect all promising candidates of character regions. The third module eliminates the plate characters that do not satisfy the plate specifications. In our experiments, the system can recognize plates over 38 frames per second with a resolution of 640 times 480 pixels on a 3-GHz Intel Pentium 4 personal computer

BiXid

Often, independent organizations define and advocate different XML formats for a similar purpose and, as a result, application programs need to mutually convert between such formats. Existng XML transformation languages, such as XSLT and XDuce, are unsatisfactory for this purpose since we would have to write, e.g., two programs for the forward and the backward transformations in case of two formats, incur high developing and maintenance costs.This paper proposes the bidirectional XML transformation language biXid, allowing us to write only one program for both directions of conversion. Our language adopts a common paradigm programming-by-relation , where a program defines a relation over documents and transforms a document to another in a way satisfying this relation. Our contributions here are specific language features for facilitating realistic conversions whose target formats are loosely in parallel but have many discrepancies in details. Concretely, we (1) adopt XDuce-style regular expression patterns for describing and analyzing XML structures, (2) fully permit ambiguity for treating formats that do not have equivalent expressivenesses, and (3) allow non-linear pattern variables for expressing non-trivial transformations that cannot be written only with linear patterns, such as conversion between unordered and ordered data.We further develop an efficient evaluation algorithm for biXid, consisting of the "parsing" phase that transforms the input document to an intermediate "parse tree" structure and the "unparsing" phase that transforms it to an output document. Both phases use a variant of finite tree automata for performing a one-pass scan on the input or the parse tree by using a standard technique that "maintains the set of all transitable states." However, the construction of the "unparsing" phase is challenging since ambiguity causes different ways of consuming the parse tree and thus results in multiple possible outputs that may have different structures.We have implemented a prototype system of biXid and confirmed that it has enough expressiveness and a linear-time performance from experiments with several realistic bidirectional transformations including one between vCard-XML and ContactXML.