941 resultados para structural test


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结构性测试是标识测试用例的基本方法之一.由于程序语言的复杂性以及被测程序的多样性,自动生成结构测试数据的一种有效方法是根据程序运行结果指导生成过程,通过不断迭代,生成符合要求的测试数据集.提出一种基于Messy GA的结构测试数据自动生成方法,将测试覆盖率表示为测试输入集X的函数F(X),并利用Messy GA不需要染色体模式排列的先验知识即可进行优化求解的性质对F(X)的进行迭代寻优,进一步提高了搜索的并行性,并最终提高测试覆盖率.对一组标准测试程序和若干实际应用程序的实验结果表明,较之现有基于遗传算法的生成方法,该方法能够以更高的效率生成更高质量的测试数据,并适用于较大规模的程序.

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Prototype validation is a major concern in modern electronic product design and development. Simulation, structural test, functional and timing debug are all forming parts of the validation process, although very often addressed as dissociated tasks. In this paper we describe an integrated approach to board-level prototype validation, based on a set of mandatory/optional BST instructions and a built-in controller for debug and test, that addresses the late mentioned tasks as inherent parts of a whole process

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Dynamically reconfigurable SRAM-based field-programmable gate arrays (FPGAs) enable the implementation of reconfigurable computing systems where several applications may be run simultaneously, sharing the available resources according to their own immediate functional requirements. To exclude malfunctioning due to faulty elements, the reliability of all FPGA resources must be guaranteed. Since resource allocation takes place asynchronously, an online structural test scheme is the only way of ensuring reliable system operation. On the other hand, this test scheme should not disturb the operation of the circuit, otherwise availability would be compromised. System performance is also influenced by the efficiency of the management strategies that must be able to dynamically allocate enough resources when requested by each application. As those resources are allocated and later released, many small free resource blocks are created, which are left unused due to performance and routing restrictions. To avoid wasting logic resources, the FPGA logic space must be defragmented regularly. This paper presents a non-intrusive active replication procedure that supports the proposed test methodology and the implementation of defragmentation strategies, assuring both the availability of resources and their perfect working condition, without disturbing system operation.

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Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper.

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The human connectome has recently become a popular research topic in neuroscience, and many new algorithms have been applied to analyze brain networks. In particular, network topology measures from graph theory have been adapted to analyze network efficiency and 'small-world' properties. While there has been a surge in the number of papers examining connectivity through graph theory, questions remain about its test-retest reliability (TRT). In particular, the reproducibility of structural connectivity measures has not been assessed. We examined the TRT of global connectivity measures generated from graph theory analyses of 17 young adults who underwent two high-angular resolution diffusion (HARDI) scans approximately 3 months apart. Of the measures assessed, modularity had the highest TRT, and it was stable across a range of sparsities (a thresholding parameter used to define which network edges are retained). These reliability measures underline the need to develop network descriptors that are robust to acquisition parameters.

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The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

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The problem of structural system identification when measurements originate from multiple tests and multiple sensors is considered. An offline solution to this problem using bootstrap particle filtering is proposed. The central idea of the proposed method is the introduction of a dummy independent variable that allows for simultaneous assimilation of multiple measurements in a sequential manner. The method can treat linear/nonlinear structural models and allows for measurements on strains and displacements under static/dynamic loads. Illustrative examples consider measurement data from numerical models and also from laboratory experiments. The results from the proposed method are compared with those from a Kalman filter-based approach and the superior performance of the proposed method is demonstrated. Copyright (C) 2009 John Wiley & Sons, Ltd.

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In this paper, we extend the heterogeneous panel data stationarity test of Hadri [Econometrics Journal, Vol. 3 (2000) pp. 148–161] to the cases where breaks are taken into account. Four models with different patterns of breaks under the null hypothesis are specified. Two of the models have been already proposed by Carrion-i-Silvestre et al.[Econometrics Journal,Vol. 8 (2005) pp. 159–175]. The moments of the statistics corresponding to the four models are derived in closed form via characteristic functions.We also provide the exact moments of a modified statistic that do not asymptotically depend on the location of the break point under the null hypothesis. The cases where the break point is unknown are also considered. For the model with breaks in the level and no time trend and for the model with breaks in the level and in the time trend, Carrion-i-Silvestre et al. [Econometrics Journal, Vol. 8 (2005) pp. 159–175]showed that the number of breaks and their positions may be allowed to differ acrossindividuals for cases with known and unknown breaks. Their results can easily be extended to the proposed modified statistic. The asymptotic distributions of all the statistics proposed are derived under the null hypothesis and are shown to be normally distributed. We show by simulations that our suggested tests have in general good performance in finite samples except the modified test. In an empirical application to the consumer prices of 22 OECD countries during the period from 1953 to 2003, we found evidence of stationarity once a structural break and cross-sectional dependence are accommodated.

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The hybrid test method is a relatively recently developed dynamic testing technique that uses numerical modelling combined with simultaneous physical testing. The concept of substructuring allows the critical or highly nonlinear part of the structure that is difficult to numerically model with accuracy to be physically tested whilst the remainder of the structure, that has a more predictable response, is numerically modelled. In this paper, a substructured soft-real time hybrid test is evaluated as an accurate means of performing seismic tests of complex structures. The structure analysed is a three-storey, two-by-one bay concentrically braced frame (CBF) steel structure subjected to seismic excitation. A ground storey braced frame substructure whose response is critical to the overall response of the structure is tested, whilst the remainder of the structure is numerically modelled. OpenSees is used for numerical modelling and OpenFresco is used for the communication between the test equipment and numerical model. A novel approach using OpenFresco to define the complex numerical substructure of an X-braced frame within a hybrid test is also presented. The results of the hybrid tests are compared to purely numerical models using OpenSees and a simulated test using a combination of OpenSees and OpenFresco. The comparative results indicate that the test method provides an accurate and cost effective procedure for performing
full scale seismic tests of complex structural systems.

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PURPOSE:

To determine the test-retest variability in perimetric, optic disc, and macular thickness parameters in a cohort of treated patients with established glaucoma.

PATIENTS AND METHODS:

In this cohort study, the authors analyzed the imaging studies and visual field tests at the baseline and 6-month visits of 162 eyes of 162 participant in the Glaucoma Imaging Longitudinal Study (GILS). They assessed the difference, expressed as the standard error of measurement, of Humphrey field analyzer II (HFA) Swedish Interactive Threshold Algorithm fast, Heidelberg retinal tomograph (HRT) II, and retinal thickness analyzer (RTA) parameters between the two visits and assumed that this difference was due to measurement variability, not pathologic change. A statistically significant change was defined as twice the standard error of measurement.

RESULTS:

In this cohort of treated glaucoma patients, it was found that statistically significant changes were 3.2 dB for mean deviation (MD), 2.2 for pattern standard deviation (PSD), 0.12 for cup shape measure, 0.26 mm for rim area, and 32.8 microm and 31.8 microm for superior and inferior macular thickness, respectively. On the basis of these values, it was estimated that the number of potential progression events detectable in this cohort by the parameters of MD, PSD, cup shape measure, rim area, superior macular thickness, and inferior macular thickness was 7.5, 6.0, 2.3, 5.7, 3.1, and 3.4, respectively.

CONCLUSIONS:

The variability of the measurements of MD, PSD, and rim area, relative to the range of possible values, is less than the variability of cup shape measure or macular thickness measurements. Therefore, the former measurements may be more useful global measurements for assessing progressive glaucoma damage.

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In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.

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This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

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There are several techniques to characterize the elastic modulus of wood and those currently using the natural frequencies of vibration stand out as they are non-destructive techniques, producing results that can be repeated and compared over time. This study reports on the effectiveness of the testing methods based on the natural frequencies of vibration versus static bending to obtain the elastic properties of reforested structural wood components usually employed in civil construction. The following components were evaluated: 24 beams of Eucalyptus sp. with nominal dimensions (40 x 60 x 2.000 mm) and 14 beams of Pinus oocarpa with nominal dimensions (45 x 90 x 2.300 mm) both without treatment; 30 boards with nominal dimensions (40 x 240 x 2.010 mm) and 30 boards with nominal dimensions (40 x 240 x 3.050 mm), both of Pinus oocarpa and with chromate copper arsenate (CCA) preservative treatment. The results obtained in thiswork show good correlation when compared to the results obtained by the static bending mechanical method, especially when applying the natural frequency of longitudinal vibration. The use of longitudinal frequency was reliable and practical, therefore recommended for determining the modulus of elasticity of wood structural elements. It was also found that no specific support is needed for the specimens using the longitudinal frequency, as well as no previous calibrations, reducing the execution time and enabling to test many samples.

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Semi-active damping devices have been shown to be effective in mitigating unwanted vibrations in civil structures. These devices impart force indirectly through real-time alterations to structural properties. Simulating the complex behavior of these devices for laboratory-scale experiments is a major challenge. Commercial devices for seismic applications typically operate in the 2-10 kN range; this force is too high for small-scale testing applications where requirements typically range from 0-10 N. Several challenges must be overcome to produce damping forces at this level. In this study, a small-scale magneto-rheological (MR) damper utilizing a fluid absorbent metal foam matrix is developed and tested to accomplish this goal. This matrix allows magneto-rheological (MR) fluid to be extracted upon magnetic excitation in order to produce MR-fluid shear stresses and viscosity effects between an electromagnetic piston, the foam, and the damper housing. Dampers for uniaxial seismic excitation are traditionally positioned in the horizontal orientation allowing MR-fluid to gather in the lower part of the damper housing when partially filled. Thus, the absorbent matrix is placed in the bottom of the housing relieving the need to fill the entire device with MR-fluid, a practice that requires seals that add significant unwanted friction to the desired low-force device. The damper, once constructed, can be used in feedback control applications to reduce seismic vibrations and to test structural control algorithms and wireless command devices. To validate this device, a parametric study was performed utilizing force and acceleration measurements to characterize damper performance and controllability for this actuator. A discussion of the results is presented to demonstrate the attainment of the damper design objectives.