Integrated health monitoring for a steel beam : an experimental study

Civil infrastructures begin to deteriorate once they are built and used. Detecting damages in a structure to maintain its safety is a topic that has received considerable attention in the literature in recent years. Many methods are developed, including global vibration-based methods and local GW-based methods. The global vibration-based method uses changes in modal properties to detect damage. The advantage of this approach is that the vibration properties are straightforward to be measured. The disadvantage of this method is that it might not be sensitive to small damage. On the other hand, local method, such as the guided waves (GW) based method is sensitive to small damage, but its sensing range is small. In this paper, an integrated structural health monitoring test scheme is developed to detect damage in a steel beam. Different saw cuts of various depths are made to simulate crack damage. Vibration tests and guided wave tests are conducted after each cut. The vibration method is used to detect the overall condition change of the beam, whereas the GW method is used to locate and quantify the damage. Experimental results show that the integrated method is efficient to detect and quantify local crack damage in steel structures and its influence on the global structure conditions

Debond detection in RC structures using piezoelectric materials

This paper presents a technique to detect the delamination between the steel bars and concrete in the reinforced concrete structures. The piezoelectric components are mounted on reinforcing bars that are embedded in RC structures as sensors and actuators to generate and record the signal, which is sensitive to the delamination between the steel bars and concrete. The experimental study is carried out on a concrete slab with different debonds between the rebars and concrete. The test results show that the delamination between the rebars and concrete can be detected with the embedded piezoelectric sensors and actuators.<br /

UAV-Assisted Wireless Powered Cooperative Mobile Edge Computing:Joint Offloading, CPU Control, and Trajectory Optimization

This article investigates the unmanned-aerial-vehicle (UAV)-enabled wireless powered cooperative mobile edge computing (MEC) system, where a UAV installed with an energy transmitter (ET) and an MEC server provides both energy and computing services to sensor devices (SDs). The active SDs desire to complete their computing tasks with the assistance of the UAV and their neighboring idle SDs that have no computing task. An optimization problem is formulated to minimize the total required energy of UAV by jointly optimizing the CPU frequencies, the offloading amount, the transmit power, and the UAV’s trajectory. To tackle the nonconvex problem, a successive convex approximation (SCA)-based algorithm is designed. Since it may be with relatively high computational complexity, as an alternative, a decomposition and iteration (DAI)-based algorithm is also proposed. The simulation results show that both proposed algorithms converge within several iterations, and the DAI-based algorithm achieve the similar minimal required energy and optimized trajectory with the SCA-based one. Moreover, for a relatively large amount of data, the SCA-based algorithm should be adopted to find an optimal solution, while for a relatively small amount of data, the DAI-based algorithm is a better choice to achieve smaller computing energy consumption. It also shows that the trajectory optimization plays a dominant factor in minimizing the total required energy of the system and optimizing acceleration has a great effect on the required energy of the UAV. Additionally, by jointly optimizing the UAV’s CPU frequencies and the amount of bits offloaded to UAV, the minimal required energy for computing can be greatly reduced compared to other schemes and by leveraging the computing resources of idle SDs, the UAV’s computing energy can also be greatly reduced

Label Transfer from APOGEE to LAMOST: Precise Stellar Parameters for 450,000 LAMOST Giants

In this era of large-scale stellar spectroscopic surveys, measurements of stellar attributes ("labels," i.e. parameters and abundances) must be made precise and consistent across surveys. Here, we demonstrate that this can be achieved by a data-driven approach to spectral modeling. With The Cannon, we transfer information from the APOGEE survey to determine precise Teff, log g, [Fe/H], and [$\alpha$/M] from the spectra of 450,000 LAMOST giants. The Cannon fits a predictive model for LAMOST spectra using 9952 stars observed in common between the two surveys, taking five labels from APOGEE DR12 as ground truth: Teff, log g, [Fe/H], [\alpha/M], and K-band extinction $A_k$. The model is then used to infer Teff, log g, [Fe/H], and [$\alpha$/M] for 454,180 giants, 20% of the LAMOST DR2 stellar sample. These are the first [$\alpha$/M] values for the full set of LAMOST giants, and the largest catalog of [$\alpha$/M] for giant stars to date. Furthermore, these labels are by construction on the APOGEE label scale; for spectra with S/N > 50, cross-validation of the model yields typical uncertainties of 70K in Teff, 0.1 in log g, 0.1 in [Fe/H], and 0.04 in [$\alpha$/M], values comparable to the broadly stated, conservative APOGEE DR12 uncertainties. Thus, by using "label transfer" to tie low-resolution (LAMOST R $\sim$ 1800) spectra to the label scale of a much higher-resolution (APOGEE R $\sim$ 22,500) survey, we substantially reduce the inconsistencies between labels measured by the individual survey pipelines. This demonstrates that label transfer with The Cannon can successfully bring different surveys onto the same physical scale.Comment: 27 pages, 14 figures. Accepted by ApJ on 16 Dec 2016, implementing suggestions from the referee reports. Associated code available at https://github.com/annayqho/TheCanno

Concurrence Vectors in Arbitrary Multipartite Quantum Systems

For a given pure state of multipartite system, the concurrence vector is defined by employing the defining representation of generators of the corresponding rotation groups. The norm of concurrence vector is considered as a measure of entanglement. For multipartite pure state, the concurrence vector is regarded as the direct sum of concurrence subvectors in the sense that each subvector is associated with a pair of particles. It is proposed to use the norm of each subvector as the contribution of the corresponding pair in entanglement of the system.Comment: 9 pages, v3, section 3 is revise

Study on fracture toughness with different thicknesses CT specimen

The material selected for this study was a WELDOX 900 steel plate. This paper analyzed the size effect of fracture toughness based on experimental results and finite element numerical simulation results. In addition, J-integrals of different thicknesses were investigated and the relational expression between them was acquired in this study. The main conclusions are as follows: Firstly, the formula between the ductile fracture toughness J0.2 and the specimen thickness was obtained. It proposed a method for predicting the fracture toughness of plane strain state using thin specimens of several thicknesses based on this formula. Secondly, the fracture toughness values of the materials were obtained by finite element numerical simulation. And it was found that the distribution of stress triaxiality near the crack tip could well explain the variation of fracture toughness with thickness

Accurate Fault Location Method of The Mechanical Transmission System of Shearer Ranging Arm

In the process of coal mine production, the fault of the mechanical transmission system of the shearer ranging arm directly affects safety production. Therefore, it is very important to achieve the accurate fault location of the shearer ranging arm. The combination method of optimized continuous complex Morlet wavelet envelope demodulation spectrum analysis and spectrum analysis is proposed. Firstly, the spectrum contrast analysis of vibration signals between the normal state and fault state is performed, which can obtain the fault characteristics frequency and preliminary fault location. Then, the optimized continuous complex Morlet wavelet envelope demodulation algorithm is proposed to extract the side-bands characteristics of vibration signals, which can obtain the rotation frequency of fault location by the contrast analysis of side-bands characteristics in normal and fault state. In the algorithm, the center frequency and bandwidth of Morlet wavelet are optimized by wavelet Shannon entropy, and the optimal scale factor can be accurately determined by spectrum contrast analysis of vibration signals in normal and fault state. Finally, the accurate gear fault location is achieved by comprehensive analysis results of optimized continuous complex Morlet wavelet envelope demodulation spectrum and spectrum contrast. The simulation signals and practical vibration signals are applied to verify the proposed accurate gear fault location method. The experiment results indicate that the center frequency and bandwidth determined by wavelet Shannon entropy make the wavelet waveform best match the fault impact signal, and the optimal scale factor can be accurately determined by spectrum contrast analysis of vibration signals in normal and fault state, and the proposed method can achieve the precise fault location of the mechanical transmission system of shearer ranging arm. It provides the method for the on-site rapid accurate fault location of the mechanical transmission syst..