Bent Cables Research Articles

Wire-tracking of bent electric cable using X-ray CT and deep active learning.

We have demonstrated a quantification of all component wires in a bent electric cable, which is necessary for discussion of cable products in actual use cases. Quantification became possible for the first time because of our new technologies for image analysis of bent cables. In this paper, various image analysis techniques to detect all wire tracks in a bent cable are demonstrated. Unique cross-sectional image construction and deep active learning schemes are the most important items in this study. These methods allow us to know the actual state of cables under external loads, which makes it possible to elucidate the mechanisms of various phenomena related to cables in the field and further improve the quality of cable products.

Defect Detection for the Insulation Layer of Bent Aircraft Cables Based on Ultrasonic Guided Waves

The damage of aircraft cables is a major issue in the aerospace industry, which usually starts from insulation layer defect and can lead to serious casualties and financial losses. In this article, a method for defect detection for the insulation layer of bent aircraft cables is proposed, which is based on ultrasonic guided waves (UGWs). The propagation characteristics of UGWs in bent cables were studied by simulation and experiments, and wavelet packet decomposition (WPD) was used for feature extraction of the detection signals to distinguish bending and defects in the insulation layer. The experimental results show that the method is able to detect and locate both bending and defects (abrasion and cut) in the insulation layer. The maximum relative error in bending and defect localization does not exceed 0.3%.

A Fast Prediction Approach of Radiated Emissions From Closely-Spaced Bent Cables in Motor Driving System

Three-phase cables in a motor driving system are the major ways of electromagnetic radiation, which result in potential interference to the nearby electronic equipment on electric vehicle. Numerical simulation of radiated emissions from cables is time-consuming, which becomes insufficient to compute large numbers of cables for actual applications. Hence, this article proposes a fast prediction approach that can highly improve the computational efficiency. Since cables are often close to each other and arbitrarily bent in the real application due to confined working space, the influence of proximity effects caused by closely-spaced cables on radiated emissions is also considered in the calculation model by multi-transmission line and Hertzian dipole theories. Besides, an equivalent model is presented to characterize the measured motor impedance. On the basis of the proposed cables model, a complete motor driving system model is originally developed by integrating a radiated electromagnetic interference (EMI) source model of inverter and a load equivalent model of motor impedance. The system model is of vital value to identify the mechanism concerning radiated EMI issues on electric vehicles and efficiently evaluated in the end. Both numerical simulations and experiments are conducted for the validation of proposed approach, which show that the proposed approach can save over 90% computational time with desired evaluation accuracy.

Wire in the Cable-Driven System of Surgical Robot

During the evolution of the surgical robot, cable plays an important role. It translates motion and force precisely from surgeon’s hand to the tool’s tips. In the paper, the vertical wires, the composition of cable, are mathematically modeled from a geometric point of view. The cable structure and tension are analyzed according to the characteristics of wire screw twist. The structural equations of the wires in different positions are derived for both non-bent cable and bent cable, respectively. The bending moment formula of bent cable is also obtained. This will help researchers find suitable cable and design more matched pulley.

A Statistical Investigation to Monitor and Understand Atmospheric CFC Decline with the Spatial-longitudinal Bent-cable Model

Concerns about the concentrations of chlorofluorocarbons (CFCs) in the atmosphere are based on their effects on the ozone layer by catalytically destroying ozone. The recent steady decline in atmospheric concentration of CFC could be a direct result of the Montr\'eal Protocol's ban on CFC products, in effect since 1989. However, CFCs have long atmospheric residence times because of their low chemical reactivity, and as a consequence have already been distributed globally. To study the spatial effects and extent of the decline, we apply the proposed spatial-longitudinal bent-cable model to CFC data observed over a global detection network. The bent cable is a parametric regression model to study data that exhibits a trend change. It comprises two linear segments to describe the incoming and the outgoing phases, joined by a quadratic bend to model the transition period. For spatial longitudinal data, measurements taken over time are nested within spatially dependent locations. Here, it is useful to extend the existing longitudinal bent-cable regression to handle spatial effects. We do so in a hierarchical Bayesian framework by allowing the error terms to be correlated across space. The methodology is illustrated with applications to CFC-11 and 12 data. Our analysis reveals that: (a) there is a strong spatial relationship among all the monitoring locations across the globe; (b) both CFC-11 and CFC-12 increased significantly before entering into a transition zone; (c) after completing the transition, CFC-11 has been decreasing significantly from the atmosphere, but a slow (insignificant) decrease for CFC-12 is observed; and (d) it may take almost 5 times longer to diminish CFC-12 from the atmosphere compared to CFC-11.

Bent‐cable regression with autoregressive noise

AbstractMotivated by time series of atmospheric concentrations of certain pollutants the authors develop bent‐cable regression for autocorrelated errors. Bent‐cable regression extends the popular piecewise linear (broken‐stick) model, allowing for a smooth change region of any non‐negative width. Here the authors consider autoregressive noise added to a bent‐cable mean structure, with unknown regression and time series parameters. They develop asymptotic theory for conditional least‐squares estimation in a triangular array framework, wherein each segment of the bent cable contains an increasing number of observations while the autoregressive order remains constant as the sample size grows. They explore the theory in a simulation study, develop implementation details, apply the methodology to the motivating pollutant dataset, and provide a scientific interpretation of the bent‐cable change point not discussed previously. The Canadian Journal of Statistics 38: 386–407; 2010 © 2010 Statistical Society of Canada

Bent-Cable Regression Theory and Applications

We use the so-called “bent-cable” model to describe natural phenomena that exhibit a potentially sharp change in slope. The model comprises two linear segments, joined smoothly by a quadratic bend. The class of bent cables includes, as a limiting case, the popular piecewise-linear model (with a sharp kink), otherwise known as the broken stick. Associated with bent-cable regression is the estimation of the bend-width parameter, through which the abruptness of the underlying transition may be assessed. We present worked examples and simulations to demonstrate the regularity and irregularity of bent-cable regression encountered in finite-sample settings. We also extend existing bent-cable asymptotics that previously were limited to the basic model with known linear slopes of 0 and 1. Practical conditions on the design are given to ensure regularity of the full bent-cable estimation problem if the underlying bend segment has nonzero width. Under such conditions, the least-squares estimators are shown to be consistent and to asymptotically follow a multivariate normal distribution. Furthermore, the deviance statistic (or the likelihood ratio statistic, if the random errors are normally distributed) is shown to have an asymptotic chi-squared distribution.

Asymptotic theory for bent-cable regression—the basic case

We use what we call the bent-cable model to describe potential change-point phenomena. The class of bent cables includes the commonly used broken stick (a bent cable without a bend segment). Theory for least-squares (LS) estimation is developed for the basic bent cable, whose incoming and outgoing linear phases have slopes 0 and 1, respectively, and are joined smoothly by a quadratic bend. Conditions on the design are given to ensure regularity of the estimation problem, despite non-differentiability of the model's first partial derivatives (with respect to the covariate and model parameters). Under such conditions, we show that the LS estimators (i) are consistent, regardless of a zero or positive true bend width; and (ii) asymptotically follow a bivariate normal distribution, if the underlying cable has all three segments. In the latter case, we show that the deviance statistic has an asymptotic chi-squared distribution with two degrees of freedom.

Discussion of “ Internal Friction Due to Wire Twist in Bent CABLE ” by Oleg G. Vinogradov, Irfan S. Atatekin (Sept., 1986)

Discussion of “ <i>Internal Friction Due to Wire Twist in Bent CABLE</i> ” by Oleg G. Vinogradov, Irfan S. Atatekin (Sept., 1986)

Helical Wire Stresses in Bent Cables

An approximate theory is developed to determine the compound stress state existing in helical wires of a cable bent through a planar circular arc. Approximations arise through the treatment of the frictional interface between layers of wires. Furthermore, all materials are assumed to be linearly elastic. The model does, however, recognize geometric nonlinearities in terms of the strain-displacement relations for wire elongation and curvature. The theory presented reveals the nature of axial, bending and torsional shearing stresses produced in round helical wires. Comparisons with experimental data show reasonable agreement.