查看更多>>摘要：Cement-based sensors with magneto-aligned nickel fillers have the proven capability to significantly enhance piezoresistivity compared with the sensors with randomized fillers. In this paper, the influence of particle morphology and concentration of nickel particles on the piezoresistive and mechanical properties of cement-based sensors, treated with and without magnetic field intervention, are investigated experimentally. Five categories of nickel particles with different average diameters are type N50 (50 nm), N500 (0.5 mu m), F(1 mu m x 20 mu m flake), T (5 mu m) and U (25 mu m). The obtained results indicate that the application of magnetic field enhances most of the piezoresistive performance and yields best piezoresistivity for the samples with type T nickel powder(.) Anisotropic piezoresistivity can be achieved under a very low filler content (0.1 vol%) in N50 nano-scale nickel powder and cement composite, followed by the N500 and T nickel particles in 5 vol% content. Small particles with lower content have similar piezoresistive performance to the samples with large particles and higher concentration. One half of the samples can achieve high giant gauge factor (GF) of over 500, two-thirds of which are aligned by magnetic field with anisotmpic piezoresistive property. Samples with 5 vol% type T nickel content has the highest GF value, followed by the sample with 5 vol% type F nickel flakes and 10 vol% type U nickel powder. It is also found that mechanical strength decreases with the increase of particle concentration.
查看更多>>摘要：Electromagnetic radiation (EMR) waveforms contain rich information on coal fracture law, which is of great value to the refined study of their characteristics. In this paper, the Hilbert-Huang transform (HHT) method is used to analyze and process EMR waveform of coal failure process. The results show that HHT method can adapt well to the nonstationary and nonlinear characteristics of EMR waveform. It adaptively decomposes EMR waveforms by empirical mode decomposition (EMD), extracts the intrinsic mode function (IMF) characteristics of EMR waveforms, and obtains the law of instantaneous energy changes of EMR waveforms. At the same time, EMR waveform energy is quantitatively expressed on the three-dimensional Hilbert energy spectrum (time-frequency-energy distribution), and the refined features of EMR waveform signal are effectively extracted. The instantaneous energy of EMR and the three-dimensional Hilbert energy spectrum processed by HHT method more easily describe the fracture law of coal body. Compared with conventional characteristic parameters, such as EMR amplitude and dominant frequency, the identification degree of the precursor characteristics of coal body instability is greatly improved. Among the short-term Fourier transform (STFT), wavelet transform (WT) and HHT nonstationary signal processing methods, HHT method has an improved adaptability and superiority and can reveal the characteristics of coal deformation and failure more carefully and accurately, which provides a new means for better using and improving EMR method to monitor coal instability and failure.
Bansal, TusharTalakokula, VisalakshiMathiyazhagan, Kaliyan
17页
查看更多>>摘要：As concrete is one of the most common material used in the construction industry, it is essential to monitor and predict the strength development during curing/hydration process in order to avoid unexpected catastrophic failure during the construction process. Hence, this paper presents equivalent structural parameters-based strength monitoring and prediction of ternary blended concrete system using machine learning (ML). Different piezo configurations were adopted to check their sensitivity and suitability in real-life applications and ML models were developed based on the extracted impedance data acquired using piezo sensors. Comparing the sensitivity of different piezo configurations, embedded configuration performed the best during the hydration process and strength gain. Furthermore, fine gaussian support vector machine (SVM) model best predicted the compressive strength with an error of less than 2% and coefficient of determination (R-2) value of 1 and 0.99 for ternary blended and conventional concrete system, respectively.
查看更多>>摘要：In recent years, surface defect detection methods based on deep learning have been widely used. A conflict between speed and accuracy, however, still exists. In this paper, a steel surface defect detector, DCC-CenterNet, is proposed to achieve the best speed-accuracy trade-off. This detector uses keypoint estimation to locate center points and regresses all other defect properties. Firstly, a dilated feature enhancement model is proposed to enlarge the receptive field of the detector. Secondly, a new centerness function center-weight is proposed to make the keypoint estimation more accurate. Then, the CIoU loss that considers the overlap area and aspect ratio of the defect is adopted in the size regression. Finally, the results of experiments show that the accuracy of DCCCenterNet can reach 79.41 mAP, and the running speed FPS is 71.37 with input size 224 x 224 on the NEU-DET steel defect dataset. And it reaches 61.93 mAP on the GC10-DET steel sheet surface defect dataset at a running speed of 31.47 FPS with input size 512 x 512. It demonstrates that the developed detector can detect steel surface defects efficiently and effectively.
查看更多>>摘要：Differential scanning calorimetry (DSC) is a powerful technique to study temperature induced phase transitions by monitoring the heat capacity changes. Traditional ways of DSC data analysis require manual baseline subtraction and peak analysis, which inevitably leads to errors caused by human bias. To tackle this long-standing challenge, we propose an automated method for DSC signal extraction and baseline estimation based on semi supervised machine learning. We implement an exponential modified Gaussian mixture (EMGM) model to identify the signal of interest, and use the expectation-maximization algorithm to optimize the log-likelihood of the model. This method is then combined with the iterative polynomial fitting method for baseline allocation. One advantage of the method is not requiring the knowledge of the signal, as it is learned through matrix factorization. We demonstrate the method's efficacy using three types of protein data measured by distinctive DSC instruments. It can effectively identify the signals of interest from the raw signal and perform proper baseline subtraction. Furthermore, the program can accurately obtain the thermodynamic parameters from the peak signals for thermal characterization. In summary, this work's automated signal processing method improves the speed and accuracy of the DSC data interpretation. The code and data for this work can be found at: https://g ithub.com/shuyu-wang/DSC_data_analysis/.
查看更多>>摘要：There is a growing demand for an efficient noninvasive method for monitoring stabilization sites. Geophysical monitoring method was applied in a pilot site. Electrical resistivity tomography (ERT) and time-domain induced polarization (TDIP) surveys showed that the topsoil and stabilized soil exhibited an electrical resistivity of 335.7 +/- 251.8 and 74.8 +/- 16.9 O-m, respectively, and a chargeability of 11.7 +/- 7.6 and 6.0 +/- 2.3 mV/V, respectively. Both methods distinguished the stabilized layer and topsoil, and 3D ERT and TDIP provided additional infor-mation related to the long-term stability of the stabilized site. The influence of the electrode type on electrical resistivity and chargeability noise was negligible. As the water content in the soil increased, the electrical resistivity and chargeability decreased in the stabilized soil, while chargeability increased at a water content of 20-30% in the topsoil. This study highlights the potential of geophysical methods for monitoring stabilized sites.
查看更多>>摘要：The real-time high-accuracy orbit and clock of the GNSS (Global Navigation Satellite System) are one of the most essential corrections for the real-time kinematic precise orbit determination (POD) mode and reduced-dynamic POD mode for Low Earth Orbit (LEO) satellites. This work is devoted to initially achieve the real-time POD with the two modes and compare their performance. Numerical results showed that (1) the average accuracy improvement of the real-time reduced-dynamic POD relative to the real-time kinematic POD is about 46% on the condition that the number of observable GPS satellites is less than 6; (2) Comparing with the real-time kinematic POD, the real-time reduced-dynamic orbit determination by applying dynamical constraints can improve the accuracy (maximum 12%) of LEO POD and reduce the convergence time (maximum 20%); (3) in most circumstances, the accuracy of real-time kinematic POD and reduced-dynamic POD for LEO are better than 11 cm and 9 cm, respectively, and the reduced-dynamic POD performs more robust against the kinematic POD.
查看更多>>摘要：Uncertainties of refractive and group index in dispersion measurement by spectrally resolved white light interferometry are deeply analyzed. First, the contribution to uncertainty of the different parameters affecting both indices is identified. Afterwards, results are presented for a 1.5 mm thick fused silica sample over a broad spectral range, from 400 to 1000 nm, and the effects that mostly deteriorate the measurement accuracy are established. Finally, the different contributions are quadratically combined to determine the total uncertainty of the two indices.
查看更多>>摘要：Advanced research on high-pressure metrology (HPM) has taken the field to new heights during the last 190 years. The design and development of the pressure balance (PB), a fundamental instrument, is regarded as a breakthrough development among several other technologies in the field of HPM during this era. The primary standards of HPM, maintained by most of the National Metrology Institutes (NMIs), are based on PBs. The present paper presents a systematic review of the research carried out in HPM. A long chain of several innovative and novel approaches adopted by different researchers in the development process of PB is discussed. The retrospective study presented here includes the working principles of pressure measuring devices; contemporary techniques; design of PBs; implications of recently adopted redefinition of SI units on pressure parameter; summary of existing Calibration and Measurement Capabilities (CMCs) in high pressure range, published in BIPM Key Comparison Database (KCDB) by different NMIs and future of PBs. The present study carried out is an attempt to include the past, present, and future of PBs. The review, therefore, presents a consolidated and concise report on the development of HPM which should be a useful resource for researchers, engineers, scientists and metrologists for future research works.
查看更多>>摘要：The strain information and loads conditions of composite wings are important basis for aircraft health evaluation. In this paper, firstly to demonstrate the accuracy of Fiber Bragg Grating (FBG) sensors and provide guidance for the following study, experiment is carried out to study the effect of the adhesive layer thickness on the strain transfer. Then finite element analysis software ABAQUS is applied to analyze the strain distribution, and the simulation data is used to fit the pseudo-Kriging interpolation model to invert the strain information of crucial points. Finally, K-BP model is proposed by combining the interpolation model with back propagation (BP) neural network, which can be used to improve the accuracy on both strain field inversion and load identification. The results show that the proposed model can achieve great load identification results with fewer samples and optimize the interpolation parameters at the same time, which could provide important basis for evaluating the accuracy of strain field.
NSTL
Elsevier