79 research outputs found

    Enhanced Measurement of Paper Basis Weight Using Phase Shift in Terahertz Time-Domain Spectroscopy

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    THz time-domain spectroscopy has evolved as a noncontact, safe, and efficient technique for paper characterization. Our previous work adopted peak amplitude and delay time as features to determine paper basis weight using terahertz time-domain spectroscopy. However, peak amplitude and delay time tend to suffer from noises, resulting in degradation of accuracy and robustness. This paper proposes a noise-robust phase-shift based method to enhance measurements of paper basis weight. Based on Fresnel Formulae, the physical relationship between phase shift and paper basis weight is formulated theoretically neglecting multiple reflections in the case of normal incidence. The established formulation indicates that phase shift correlates linearly with paper basis weight intrinsically. Subsequently, paper sheets were stacked to fabricate the samples with different basis weights, and experimental results verified the developed mathematical formulation. Moreover, a comparison was made between phase shift, peak amplitude, and delay time with respect to linearity, accuracy, and noise robustness. The results show that phase shift is superior to the others

    Non-invasive load monitoring of induction motor drives using magnetic flux sensors

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    Existing load monitoring methods for induction machines are generally effective, but suffer from sensitivity problems at low speeds and non-linearity problems at high supply frequencies. This study proposes a new noninvasive load monitoring method based on giant magnetoresistance flux sensors to trace stray flux leaking from induction motors. Finite element analysis is applied to analyse stray flux features of test machines. Contrary to the conventional methods of measuring stator and/or rotator rotor voltage and current, the proposed method measures the dynamic magnetic field at specific locations and provides time-spectrum features (e.g. spectrograms), response time load and stator/rotor characteristics. Three induction motors with different starting loading profiles are tested at two separate test benches and their results are analysed in the time-frequency domain. Their steady features and dynamic load response time through spectrograms under variable loads are extracted to correlate with load variations based on spectrogram information. In addition, the transient stray flux spectrogram and time information are more effective for load monitoring than steady state information from numerical and experimental studies. The proposed method is proven to be a low-cost and non-invasive method for induction machine load monitoring

    Sensors, Signal, and Artificial Intelligent Processing

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    Health Monitoring for Coated Steel Belts in an Elevator System

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    This paper presents a method of health monitoring for coated steel belts in an elevator system by measuring the electrical resistance of the ropes embedded in the belt. A model on resistance change caused by fretting wear and stress fatigue has been established. Temperature and reciprocating cycles are also taken into consideration when determining the potential strength degradation of the belts. It is proved by experiments that the method could effectively estimate the health degradation of the most dangerous section as well as other ones along the whole belts

    Time-response-histogram-based feature of magnetic barkhausen noise for material characterization considering influences of grain and grain boundary under in situ tensile test

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    Stress is the crucial factor of ferromagnetic material failure origin. However, the non-destructive test methods to analyze the ferromagnetic material properties’ inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet’s inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress

    A Wireless Transient Attenuated-exponential Overpressure Beamforming with for Far-field Blast Source Localization

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    Time-domain beamforming is more suitable for blast wave transient signal than frequency-domain beamformer because wide-band spectrum of noise makes the beamforming image less clear. To avoid the gust effects and enable the location of blast source accurately, this paper proposes a new one-dimensional Far-field delay-and-sum (DAS) beamforming method with an attenuate exponential function model for wireless overpressure transient signal. In addition, we also design wireless overpressure peak and root-mean-square (RMS) directional estimators to assess the performance of the proposed new DAS beamforming method. Furthermore, the effects of the wireless pressure sensor node (WPSL) spacing, the number of WPSLs and side lobe level brought from noise on the beam width are investigated in the two estimators. The proposed formula is verified by a uniformly spaced linear sensing array, and the results verify the feasibility of the proposed method in blast source localization. This paper is conducted to provide new insight into blast source localization algorithm, and further open a door for transient blast overpressure source localization scenarios in future

    System identification-based frequency domain feature extraction for defect detection and characterization

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    Feature extraction is the key step for defect detection in Non-Destructive Evaluation (NDE) techniques. Conventionally, feature extraction is performed using only the response or output signals from a monitoring device. In the approach proposed in this paper, the NDE device together with the material or structure under investigation are viewed as a dynamic system and the system identification techniques are used to build a parametric dynamic model for the system using the measured system input and output data. The features for defect detection and characterization are then selected and extracted from the frequency response function (FRF) derived from the identified dynamic model of the system. The new approach is validated by experimental studies with two different types of NDE techniques and the results demonstrate the advantage and potential of using control engineering-based approach for feature extraction and quantitative NDE. The proposed approach offers a general framework for selection and extraction of the dynamic property-related features of structures for defect detection and characterization, and provides a useful alternative to the existing methods with a potential of improving NDE performance

    Journey to the east: Diverse routes and variable flowering times for wheat and barley en route to prehistoric China.

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    Today, farmers in many regions of eastern Asia sow their barley grains in the spring and harvest them in the autumn of the same year (spring barley). However, when it was first domesticated in southwest Asia, barley was grown between the autumn and subsequent spring (winter barley), to complete their life cycles before the summer drought. The question of when the eastern barley shifted from the original winter habit to flexible growing schedules is of significance in terms of understanding its spread. This article investigates when barley cultivation dispersed from southwest Asia to regions of eastern Asia and how the eastern spring barley evolved in this context. We report 70 new radiocarbon measurements obtained directly from barley grains recovered from archaeological sites in eastern Eurasia. Our results indicate that the eastern dispersals of wheat and barley were distinct in both space and time. We infer that barley had been cultivated in a range of markedly contrasting environments by the second millennium BC. In this context, we consider the distribution of known haplotypes of a flowering-time gene in barley, Ppd-H1, and infer that the distributions of those haplotypes may reflect the early dispersal of barley. These patterns of dispersal resonate with the second and first millennia BC textual records documenting sowing and harvesting times for barley in central/eastern China
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