查看更多>>摘要：? 2022 Elsevier LtdMetal matrix composites are an important class of materials owing to their excellent mechanical properties. The strengthening mechanisms of the composites are mainly determined by the volume fraction of the reinforcement particles. Surface composite is a category of metal matrix composites that can be easily fabricated by friction stir processing in which reinforcement particles are limited to the surface. Determination of the volume fraction is a complicated task due to the incorporation of the reinforcement particles only in the surface layer. There is no established procedure to measure the volume fraction of the reinforcement particles in the surface composites. A discrepancy of about 10–30% is reported in various volume fraction determination procedures. Investigators used various approaches to estimate the volume fraction of the surface composites. These approaches are discussed in brief with the methodology adapted and corrections for accurate estimation are also provided.
查看更多>>摘要：? 2022 Elsevier LtdA multi-mode system (MMS) is often switched among different modes which can experience great state changes. Compared with the single-mode system, fault detection for MMS is more challenging due to the diversity of states. The existing fault detection methods for MMS are mainly the data-driven based which cannot effectively combine expert knowledge with observation data. In this paper, a new multi-mode identification framework is constructed based on the evidential reasoning approach with interval reference values (ER-IRV), which can integrate thresholds of different modes. In this framework, a two-stage fault detection method is proposed. In the off-line stage, a multi-threshold optimization algorithm is developed by aggregating historical data recursively using the ER-IRV. Based on the optimized thresholds, transition processes are modeled using the membership degree of standard transitional data to steady modes. In the on-line stage, steady modes are identified by aggregating multiple attributes, and transition processes can be identified by analyzing the membership degree variation characteristics. Finally, fault detection can be realized by univariate threshold detection method and transitional slope detection method respectively. The implementation procedure of the methodology is given by a numerical example. The practical application effect is verified by a fault detection experiment on satellite turntable system.
查看更多>>摘要：? 2022 Elsevier LtdOver the past few decades, various image-based approaches for quantifying particle morphological indicators have been developed. But most of these methods are not applicable to field conditions. This study provides a fast and practical method for determining particle size and shape based on smartphone photogrammetry. Digital elevation models (DEMs) of the particles were created by using structure from motion photogrammetry and utilized to estimate the morphological characteristics of the particles. The size and shape of 110 coarse particles were determined by the proposed method and compared with the sieving method, hand measurement, and 2D image analysis method. The results show that the method is highly practical, with the measurement accuracies for particle length, width, and thickness being ?2.7% ± 6.3%, ?1.8% ± 9.9%, and 10.1% ± 11.5%, respectively. The proposed method has the potential to become a popular method for measuring particle size and shape in field conditions.
查看更多>>摘要：? 2022 Elsevier LtdA noncontact and nondestructive method based on laser ultrasound is proposed for evaluation of porosity in additive manufacturing components. The 304L stainless steel samples with porosities in the range of 0.1%–5.7 % were fabricated using selective laser melting. Laser ultrasonic surface wave was used to characterize the porosity by the wave speed, peak frequency and wavelet packet energy. The result indicates that the surface wave speed, peak frequency and wavelet packet energy are sensitive to the slight variation of porosity in the samples. Good R-squares of fitting between surface wave velocity and porosity were obtained when it considers the pore irregular morphology. The peak frequency of surface wave decreases as the disappearance of high-frequency signals induced by the scattering attenuation. The wavelet packet analysis result shows that the sum of the percentage energy of the ninth layer of wavelet packet decomposition nodes 2–4 is linearly related to the porosity, and exhibits the highest coefficient of determination (R = 0.98) among the proposed characteristics. It is concluded that the laser ultrasonic surface wave based on wavelet packet energy is recommended to be a promising candidate for the quantitative nondestructive evaluation of the porosity of additive manufacturing components.
Antonio Santoyo-Ramon J.Casilari E.Manuel Cano-Garcia J.
12页
查看更多>>摘要：? 2022 The AuthorsLast decade has witnessed a major research interest on wearable fall detection systems. Sampling rate in these detectors strongly affects the power consumption and required complexity of the employed wearables. This study investigates the effect of the sampling frequency on the efficacy of the detection process. For this purpose, we train a convolutional neural network to directly discriminate falls from conventional activities based on the raw acceleration signals captured by a transportable sensor. Then, we analyze the changes in the performance of this classifier when the sampling rate is progressively reduced. In contrast with previous studies, the detector is tested against a wide set of public repositories of benchmarking traces. The quality metrics achieved for the different frequencies and the analysis of the spectrum of the signals reveal that a sampling rate of 20 Hz can be enough to maximize the effectiveness of a fall detector.
查看更多>>摘要：? 2022 The Author(s)In this paper, the monitoring method based on slow feature analysis and the root cause diagnosis based on transfer entropy are proposed. Different from the traditional methods, this paper performing online modelling to improve the adaptability to different data features and the dynamics of the model. A Dynamic Dissimilarity Index (DDI) is proposed to construct a dynamic online sub-block partitioning model. For process monitoring of multidimensional quality variables, a weighted fusion method is proposed to integrate multiple models so that the monitoring conclusions include the quality changes of the process. The fault variables are identified for quality-related faults, and the traditional method is improved by proposing a transfer entropy method with time lag parameters added to optimize the fault causality diagram. Finally, the study of real chemical processes shows that the proposed method gives more accurate and richer monitoring conclusions and can find the root cause more quickly and efficiently.
查看更多>>摘要：? 2022 Elsevier LtdPlanar eddy current (EC) probe is one of the most important EC probe for detecting the defects in conductive parts. A novel planar differential excitation EC probe are proposed and its excitation coil is obtained by the topological transformation combining the fractal Koch curve. To explore the right combination of the excitation coil and pickup coil and compare the performance of the probes, ten different configurations of the EC probe are studied by the simulations and experiment. The results show that the best pickup coil of each excitation is with the same shape and size of the excitation; The Koch excitation and Koch pickup probe have higher sensitivity for 3mm and 5mm length defects in the special direction than other configurations.
查看更多>>摘要：? 2022 Elsevier LtdThe latest research directions of combustion flow field visualisation and combustion diagnosis have been extended to the development of non-contact, multi-parameter measurement methods for qualitative analysis and multi-dimensional visualisation. Velocity and temperature are important parameters that reflect the characteristics of the combustion flow field and affect the combustion dynamics and combustion mechanism, which have become the keys to characterising and diagnosing the combustion process. Three-dimensional (3D) velocity and temperature fields of combustion were reconstructed in combination with particle image velocimetry (PIV) and deflection tomography temperature measurement methods, and swirl combustion characteristics were studied. A non-premixed burner was designed to generate a swirling flame, and an experimental system was constructed for the simultaneous measurement of velocity and temperature to acquire tracer particles and Moiré fringe images. A 3D particle recognition technology and cross-correlation algorithm were used to reconstruct a 3D combustion velocity field. The fringe displacement analytical technique and deflection angle correction iterative tomography algorithm were used to reconstruct a 3D temperature field. The effects of different swirl numbers and swirl vane positions on the characteristics of the swirl flame shape, velocity distribution, and temperature distribution were investigated. The combustion reaction and field process evolution were explained. Certain characteristics, including heat and mass transfer and flow field transport of swirling combustion, were analysed. The measurement errors were discussed.
查看更多>>摘要：? 2022 Elsevier LtdReal-time monitoring and manipulating various liquids in the microflow channels have great potentials in micro total analysis system. A novel microfluidics volume optical monitoring system (MVOMS) is proposed. Functional channels embedded with hollow cylindrical waveguide (HCW) are integrated in MVOMS, which is convenient to realize the real-time monitoring and manipulating microfluidic. The microfluidic volume can be monitored in real time and the sensitivity can reach 20.0 dB/μL. In addition, the MVOMS can realize the monitoring of various liquid for the designed sensor structure is insensitive to the refractive index of liquid. The temperature cross and the pressure cross are tested that can be ignored. Microfluidic volume monitoring, delivering and mixing can be achieved in MVOMS. On this basis, we design an integrated light-driven microfluidic quantitative sampling system, which can sample a specific volume of microfluidic in microchips automatically and accurately.
查看更多>>摘要：? 2022 Elsevier LtdAmong the time frequency (TF) analysis (TFA) post-processing methods, limited by the accuracy of the estimated group delay (GD), the time-reassigned synchrosqueezing transform (TSST) and the second-order TSST (STSST) cannot provide a satisfied TFA performance for analyzing the signal with strong GD modulation. To settle this downside, the high order TSST (HTSST) is proposed. However, due to the truth that HTSST is sensitive to the plus-noise signal, the TF representation is not concentrated than the STSST. For further improving the TF resolution, a new TFA post-processing tool is proposed in this study, which named as local maximum high order time iterative synchrosqueezing (LHTIS) method. The basic idea of this technique can be divided as two steps. First, according to an iterative procedure, the TF coefficients of the high order frequency-varying signal are reassigned onto the estimated high order GD trajectory along time direction. Second, via maximizing the local TF coefficients after iterative reassignment in the first step, we rebuild a GD estimation operator to squeeze the obtained TF results. Numerical simulations are adopted to demonstrate the TF aggregation and the anti-noise property of LHTIS methodology. Via dealing with the fault signals of rolling bearings, the effectiveness of LHTIS is verified.
NSTL
Elsevier