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The mode shape-aided method provides a simple and effective way for cable force determination, which, however, requires accurate parameter identification of the cable structure. This paper proposes a phase-based video motion magnification to process the image sequences of a cable. Digital image correlations were engaged to measure the dynamic displacement–time history, through tracking the surface characteristic features of the cable. Thereafter, a frequency–domain decomposition technique was applied to extract the natural frequency and mode shape of the cable from the displacement–time history measurements. The identified cable mode shapes, along with a tensioned pinned-pinned cable model, were used to estimate the cable force. The accuracy of the proposed methodology was subsequently verified through laboratory testing on an inclined cable model and field testing on a typical hanger cable of a real-world arch bridge. Overall, the study results indicated that the proposed methodology could expediently and cost-effectively estimate the tension forces of a cable with reasonably acceptable identification accuracy. [ABSTRACT FROM AUTHOR]

Accurate detection of arrhythmia signal types is of great significance for the early detection of heart disease and its subsequent treatment. The primary purpose of this study is to explore an electrocardiogram (ECG) classification system to improve its performance and achieve excellent computing performance, especially for large sample datasets. We classified ECG signals using the Hurst exponent, which is an ECG feature extracted by multifractal detrended moving average cross-correlation analysis (MF-XDMA). In addition, we used multifractal methods such as multifractal detrended fluctuation analysis (MF-DFA), multifractal detrended cross-correlation analysis (MF-DCCA) and multifractal detrended moving average (MF-DMA) to extract the features of ECG signals, and we used a support vector machine (SVM) to classify the four types of feature data. The experimental results show that MF-XDMA-SVM has the best classification performance for atrial premature beat (APB) and bigeminy signals, which indicates that MF-XDMA-SVM is the most effective for the extraction of ECG signal sequence features among the four multifractal models. [ABSTRACT FROM AUTHOR]

The presence of intermediate supports usually imposes difficulties in identifying the tension force of stayed cables in cable-stayed bridges or hanger cables in arch bridges. This paper establishes the partial differential equations of motion of the cable and derives two numerical models with (Model 1) and without (Model 2) considering the flexural rigidity. The effects of two intermediate supports on the identification accuracy of the cable tension force are further studied analytically and experimentally. The effects of several non-dimensional parameters (e.g. damper location, support stiffness, flexural rigidity, and mode order of the cable) on the identification accuracy of the models are also investigated. It is theoretically concluded that the simplified Model 2 provides acceptable accuracy on tension force identification when the non-dimensional parameter ξ is greater than 90 (slender cables), whereas the accurate Model 1 can be applied for tension force identification at any scenarios. The feasibility of two models is further verified by three numerical examples and field tests on two real-world arch bridges. [ABSTRACT FROM AUTHOR]

This paper presents the design of a relative low-cost and more compatible autonomous helicopter system using HIROBO 50 scale as an experimental platform. Because of the limit of helicopter payload, we choose the MP2128 Autopilot and a number of sensors to build the system and the weight of instrumentation is about 500 g, much less than the payload capability of model helicopter. Thus it is feasible to design the binocular stereo-camera system to achieve full autonomous flight and the whole weight (include power) of instrumentation is about 1500 g. After getting the model of the helicopter using the subspace model identification (SMI) algorithms, we present the structure of fuzzy PID controller. [ABSTRACT FROM AUTHOR]