Curvature-based Method Research Articles

Experimental Investigation of Notch-Type Damage Identification with a Curvature-Based Method by Using a Continuously Scanning Laser Doppler Vibrometer System

This paper experimentally investigates a notch-type damage identification methodology for beams by using a continuously scanning laser Doppler vibrometer (CSLDV) system. Velocity response of a beam along a scan line under sinusoidal excitation is measured by the CSLDV system and an operating deflection shape (ODS) of the beam is obtained by the demodulation method from velocity response. The ODS of an associated undamaged beam is obtained by using a polynomial with a proper order to fit the ODS from the demodulation method. The curvature of an ODS (CODS) can be calculated with a high quality due to a dense measurement grid of the ODS. A curvature damage index (CDI) is proposed to identify a notch with a length of 1 mm along a beam and a depth of 0.9 mm under different excitation frequencies. The CDI uses differences between CODSs associated with ODSs that are obtained by the demodulation method and the polynomial fit; an auxiliary CDI obtained by averaging CDIs at different excitation frequencies is defined to further assist identification of damage. An averaging technique is applied to velocity response of the beam to reduce measurement noise. Effects of the number of averages on ODSs, CODSs, and CDIs are investigated. Four scan lines with an equal length of 151 mm and different locations with respect to the notch are used to investigate reliability of the proposed methodology. Finally, a whole scan line with a length of 555 mm along the beam is applied and the notch is successfully identified near regions with consistently high values of CDIs at different excitation frequencies; it can also be identified with the auxiliary CDI by a prominent peak at the location of the notch.

Online human moves recognition through discriminative key poses and speed-aware action graphs

Recognizing user-defined moves serves a large number of applications including sport monitoring, virtual reality or natural user interfaces (NUI). However, many of the efficient human move recognition methods are still limited to specific situations, such as straightforward NUI gestures or everyday human actions. In particular, most methods depend on a prior segmentation of recordings to both train and recognize moves. This segmentation step is generally performed manually or based on heuristics such as neutral poses or short pauses, limiting the range of applications. Besides, speed is generally not considered as a criterion to distinguish moves. We present an approach composed of a simplified move training phase that requires minimal user intervention, together with a novel online method to robustly recognize moves online from unsegmented data without requiring any transitional pauses or neutral poses, and additionally considering human move speed. Trained gestures are automatically segmented in real time by a curvature-based method that detects small pauses during a training session. A set of most discriminant key poses between different moves is also extracted in real time, optimizing the number of key poses. All together, this semi-supervised learning approach only requires continuous move performances from the user with small pauses. Key pose transitions and moves execution speeds are used as input to a novel human move recognition algorithm that recognizes unsegmented moves online, achieving high robustness and very low latency in our experiments, while also effective in distinguishing moves that differ only in speed.

A real-time vision-based hand gesture interaction system for virtual EAST

The virtual Experimental Advanced Superconducting Tokamak device (VEAST) is a very complicated 3D model, to interact with which, the traditional interaction devices are limited and inefficient. However, with the development of human-computer interaction (HCI), the hand gesture interaction has become a much popular choice in recent years. In this paper, we propose a real-time vision-based hand gesture interaction system for VEAST. By using one web camera, we can use our bare hand to interact with VEAST at a certain distance, which proves to be more efficient and direct than mouse. The system is composed of four modules: initialization, hand gesture recognition, interaction control and system settings. The hand gesture recognition method is based on codebook (CB) background modeling and open finger counting. Firstly, we build a background model with CB algorithm. Then, we segment the hand region by detecting skin color regions with “elliptical boundary model” in CbCr flat of YCbCr color space. Open finger which is used as a key feature of gesture can be tracked by an improved curvature-based method. Based on the method, we define nine gestures for interaction control of VEAST. Finally, we design a test to demonstrate effectiveness of our system.

MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internal features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The Senior Author receives financial support from Siemens GmbH Healthcare

Minimizing noise effect in curvature-based damage detection

Damage detection is essential for condition assessment of serviceability and safety of bridges. Different methods have been developed for damage detection based on static or dynamic response of bridges, among which curvature-based method attracted more and more attention as it shed light on accurate detection of damage location. Although there are many investigations contributed to this method, few of them considered the effect of measurement noise and approaches to minimize noise effect. In this paper, effect of measurement noise is investigated in the curvature-based damage detection. An approach is proposed to minimize noise effect for practical application on realistic cases. To verify its reliability and efficacy, laboratory experiment is conducted on a beam specimen, and the measured displacement is used to identify damage with the proposed approach. To illustrate the applicability for realistic bridges, this method was applied to a detailed Finite Element bridge model which also considers effects of measurement noise. The results indicate the feasibility of this method in practical application on girder bridges.

Mode shape-based damage detection in plate structure without baseline data

In this paper, a mode shape curvature-based method for detection and localization of damage in plate-like structures is described. The proposed algorithm requires only the mode shape curvature data of the damaged structure. The damage index is defined as the absolute difference between the measured curvature of the damaged structure and the smoothed polynomial representing the curvature of the healthy structure. To examine the advantages and limitations of the proposed method, several sets of numerical simulations are carried out. Simulated test cases considering different levels of damage severity, measurement noise and sensor sparsity are studied to evaluate the robustness of the method under the noisy experimental data and limited sensor data. Applicability and effectiveness of the proposed damage detection method are further demonstrated experimentally on an aluminium plate containing mill-cut damage. The modal frequencies and the corresponding mode shapes are obtained via finite element models for numerical simulations and by using a scanning laser vibrometer for the experimental study. Copyright © 2016 John Wiley & Sons, Ltd.

Damage detection for plate-like structures using generalized curvature mode shape method

Mode shape curvature-based method was originally developed to identify the damage in one-dimensional beam-like structures. In this paper, the method is generalized to fit for damage identification of plate-like structures, using two-dimensional mode shape curvatures. The modified method only requires the first few curvature mode shapes of the plate before and after damage, or only need modal information of the damaged plate if gapped smoothing technique is employed. To evaluate the effectiveness of the proposed method, numerical simulations considering various plate damage scenarios in terms of damage location, damage severity and multiple damages have been conducted, and experimental modal analysis on a steel plate with clamped and free edges is also performed to correlate with the numerical results. The final results show that the proposed method works well to detect the damage in a simple manner. For damaged structures, irregularities in their modal characterizations are induced at the places where local damages exist. Gapped smoothing technique takes advantage of smoothing functions and elevates the suggest method to be a reference-free approach. In the present study, a brief discussion has been performed and suggestions have been given concerning different smoothing functions used in the gapped smoothing technique.

A Fourth-Order Compact Finite Difference Scheme for Higher-Order PDE-Based Image Registration

AbstractImage registration is an ill-posed problem that has been studied widely in recent years. The so-called curvature-based image registration method is one of the most effective and well-known approaches, as it produces smooth solutions and allows an automatic rigid alignment. An important outstanding issue is the accurate and efficient numerical solution of the Euler-Lagrange system of two coupled nonlinear biharmonic equations, addressed in this article. We propose a fourth-order compact (FOC) finite difference scheme using a splitting operator on a 9-point stencil, and discuss how the resulting nonlinear discrete system can be solved efficiently by a nonlinear multi-grid (NMG) method. Thus after measuring the h-ellipticity of the nonlinear discrete operator involved by a local Fourier analysis (LFA), we show that our FOC finite difference method is amenable to multi-grid (MG) methods and an appropriate point-wise smoothing procedure. A high potential point-wise smoother using an outer-inner iteration method is shown to be effective by the LFA and numerical experiments. Real medical images are used to compare the accuracy and efficiency of our approach and the standard second-order central (SSOC) finite difference scheme in the same NMG framework. As expected for a higher-order finite difference scheme, the images generated by our FOC finite difference scheme prove significantly more accurate than those computed using the SSOC finite difference scheme. Our numerical results are consistent with the LFA analysis, and also demonstrate that the NMG method converges within a few steps.

Principal curvature for infrared small target detection

Small target detection in infrared image with complex background and low signal–noise ratio is an important and difficult task in the infrared target tracking system. In this paper, a principal curvature-based method is proposed. The principal curvatures of target pixels are negative and their absolute values are larger than that of background pixels and noise pixels in a Gaussian-blurred infrared image. The proposed filter takes a composite function of the curvatures for detection. An approximate model is also built for optimizing the parameters. Experimental results show that the proposed algorithm is effective and adaptable for infrared small target detection in complex background. Compared with several popular methods, the proposed algorithm demonstrates significant improvement on detection performance in terms of the parameters of signal clutter ratio gain, background suppression factor and ROC.

Adaptive sampling method for inspection planning on CMM for free-form surfaces

Coordinate measurement machines (CMMs) have been widely used in inspecting mechanical parts with higher accuracy. Both the distribution and the number of the sampled points on measurand have an important effect on the efficiency and quality of the measurement of CMMs. In this paper, an adaptive sampling method is proposed for inspection planning on CMM for free-form surface. The points are iteratively sampled from a form error model, which is constructed by superimposing appropriate form errors on the nominal data. Moreover, a modified algorithm is introduced to determine the deviation of two point sets for the improvement of the inspecting accuracy, and the inspection uncertainty is also analyzed. A comparison is performed between the proposed method and the two well-known sampling methods, which are the equi-parametric method and the patch mean Gaussian curvature-based method, both simulated and experiment results show the effectiveness and robustness of this method.

A novel curvature-based method for analyzing the second-order immobility of frictionless grasp

SUMMARYThis paper presents a new method to analyze frictionless grasp immobility based on defined surface-to-surface signed distance function. Distance function's differential properties are analyzed and its second-order Taylor expansion with respect to differential motion is deduced. Based on the non-negative condition of the signed distance function, the first- and second-order free motions are defined and the corresponding conditions for immobility of frictionless grasp are derived. As one benefit of the proposed method, the second-order immobility check can be formulated as a nonlinear programming problem. Numerical examples are used to verify the proposed method.

Quality improvement method for graded hexahedral element meshes

A procedure is presented to improve the quality of hexahedral element meshes, especially for the meshes adaptively generated using a modified grid-based method. Insertion technique and collapsing technique are proposed to modify the mesh topology and improve the quality of the degenerated elements which are on the mesh boundaries and cannot be improved by any nodes position smoothing methods. A curvature-based Laplacian smoothing method is employed to improve the shape-quality of boundary elements and ensure that the boundary characters of mesh are well preserved. A method for improving the shape-quality of the mesh surface and the initial elements which is based on the objective function of the mesh quality metric is proposed. For the mesh surface, the Condition Number of the Jacobian metric associated with the quadrangle elements is taken as the optimization objective function. For the initial elements, after smoothing with the Laplacian method, the Scaled Jacobian metric associated with the hexahedral elements is employed as the optimization objective function. The proposed optimization methods have been applied to the adaptive generation of the hexahedral element mesh using grid-based method. The effectiveness and robustness of the proposed optimization methods are tested through several complex three-dimensional models.

Background-incorporated volumetric model for patient-specific surgical simulation: a segmentation-free, modeling-free framework

Patient-specific surgical simulation imposes both practical and technical challenges. We propose a segmentation-free, modeling-free framework that creates medical volumetric models for intuitive volume deformation and manipulation in patient-specific surgical simulation. The proposed framework creates a volumetric model based upon a new form of mesh structure, a Volume Proxy Mesh (VPM). The model can be generated in two phases: the vertex placement phase and mesh improvement phase. Vertices of a VPM are assigned to an initial location by curvature-based vertex placement method, and followed by mesh improvement performed by Particle Swarm Optimization (PSO). The framework is applied to several kidney CT volume data. Using the framework, the resulting models are closely tailored to the detailed features of the datasets. Moreover, the resulting VPM meshes can support broader spectrum deformation between the manipulated organ and its surrounding tissues. Progress in the mesh quality of the final mesh also shows that PSO is feasible for mesh improvement. The framework was applied to several kidney CT volume datasets. Using the framework, the resulting models are closely tailored to the detailed features of the datasets. Moreover, the resulting VPM meshes can support broader spectrum deformation between the manipulated organ and its surrounding tissues. Evaluation of final mesh quality shows that PSO is feasible for mesh improvement.

Curvature‐ and displacement‐based finite element analyses of flexible slider crank mechanisms

AbstractThe paper presents the applications of the curvature‐ and displacement‐based finite element methods to flexible slider crank mechanisms. The displacement‐based method usually needs more elements or high‐degree polynomials to obtain highly accurate solutions. The curvature‐based method assumes a polynomial to approximate a curvature distribution, and the expressions are investigated to obtain the displacement and rotation distributions. During the process, the boundary conditions associated with displacement, rotation, and curvature are imposed, which leads the great reduction of the number of degrees of freedom that are required. The numerical results demonstrate that the errors obtained by applying the curvature‐based method are much smaller than those by applying the displacement‐based method, based on the comparison of the same number of degrees of freedom. Copyright © 2008 John Wiley & Sons, Ltd.

Correction of segmented lung boundary for inclusion of pleural nodules and pulmonary vessels in chest CT images

We propose a new curvature-based method for correcting the segmented lung boundary. Our method consists of the following steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, the segmented lung contours are corrected by lung smoothing in each axial slice. Our scan line search provides an efficient contour tracing and curvature calculation. Finally, the smoothed lung contours are corrected by 3D VOI refinement. This increases the smoothness in the z -axis without distortion of the lung boundary. Experimental results show that our method effectively incorporates the pleural nodules and pulmonary vessels into the segmentation results.