查看更多>>摘要：? 2022 Elsevier LtdSeveral factors hinder information retrieval in the medical profession. Consumers (layman people) often struggle to learn medical terms. Because medical terms are more evident to professionals, it is difficult for consumers to construct a query using medical terms. Consumers would find it easier to access relevant medical information if medical words relevant to their query were automatically added. Various kiosks use approaches using machine vision to form the user queries and monitor their health. This work proposes a hybrid approach to term selection by expanding user queries with medical terms relevant to the medical query. The selection of terms is based on fuzzy similarity reasoning based on two primary term selection strategies. WordNet semantic filtering is applied for preventing query drift, followed by the calculation of BERTScore. The retrieved documents were ranked using Okapi-BM25. For evaluation purposes, six benchmark datasets have been used: CACM, CISI, MEDLINE, ADI, FIRE, and TREC (Covid-19). The results indicate that the suggested technique outperforms the current state-of-the-art.
查看更多>>摘要：? 2022This work presents an Adaptive Large Scale Particle Image Velocimetry method (ALSPIV), which measures surface velocity of a physical model experiment with complex flow pattern. In the experiment, the eleven low-cost, high-resolution surveillance cameras are adopted to achieve a large-scale flow field in real time. The lenses of them are shined perpendicularly on water surface to minimize perspective distortion. A camera calibration method is also designed to enhance measurement accuracy. In addition, an adaptive cross-correlation algorithm can contribute to cross-correlation and a lower signal-to-noise ratio. Finally, an experimental method is employed to verify the ALSPIV method's accuracy, and the surface velocity distributions under three different steady flows are measured to demonstrate its applicability. Results show that the method is demonstrated to be a low-cost and automatic flow diagnostic tool and an accurate means of measuring surface velocities in the physical model experiments of flood propagation with complex flow patterns.
查看更多>>摘要：? 2022 Elsevier LtdAppropriate design of the components of a sensing system affords high degree of performance characteristics; this article presents the design optimization of a novel force measurement strategy created using shape memory alloy (SMA) wire using the resonance principle. SMAs are unique materials that are generally used to realize actuators and dampers in instrumentation systems, now will be found in sensors too. A resonant sensing mechanism is realized using an SMA wire with gravity bias and, its co-acting flexible member the cantilever beam. The operating phenomenon is based on the shift in resonant frequency corresponding to an applied force, and the sensing module detects force in the range of few newtons. Design procedures of the sensor are realized, the modes of the physical realization are modeled using lumped parameter technique and the force measurement system using the electromechanical resonator is validated from the experimental measurements and analytical results.
查看更多>>摘要：? 2022 Elsevier LtdAiming at the accurate detection problem of concrete pouring thickness, a solution idea of synchronous data acquisition and concrete thickness detection technology based on ultrasonic inclined plane reflection and vertical reflection of ultrasonic full pulse signal is proposed. Taking full advantage of the acoustic response characteristics of different reflection models, three-dimensional modeling and data visualization optimization scheme are formed. By combining the different depths data and local measurement data, the characteristic parameter extraction technology of different media in the borehole is formed, which lays a foundation for solving the key problem of accurate detection of laitance layer thickness. Finally, a comprehensive technical system is formed, and the technical system is applied to practical engineering. The measurement results are basically consistent with the actual situation. The practical application results show that this technology can realize the three-dimensional imaging and quantitative characterization of the medium state in the borehole during concrete pouring.
查看更多>>摘要：? 2022 Elsevier LtdIn this paper a discussion on unipolar vector-controlled speed sensorless SRM-drive is underlined. It is well known that SRM-drive requires speed/position information for its efficient control and hence, use of speed/position sensor is mandatory. As, the limitations posed by speed/position sensors are obvious therefore, there is an urgent need for some speed/position estimation algorithm for having speed sensorless operation. In literature different speed/position estimation techniques are available. Among them MRAS (Model-Reference-Adaptive-System) speed-estimators are very simple to implement and free from large LUT's (Lookup-tables). Therefore, this paper concentrates on implementation of a new MRAS based scheme for improving the performance of speed-sensorless vector controlled SRM drive. This scheme uses ‘Q0’ as the functional candidate for building the MRAS structure. Unlike existing F-MRAS scheme, the proposed sensorless scheme does not require the measured nominal or on-line estimated value of stator resistance. This scheme is totally insensitive to stator resistance of the machine which is verified by performing sensitivity-analysis to stator-resistance variations. Apart from it the given estimation scheme is less sensitive to the inductance related parameter ‘Lav’ in comparison to ‘Z-MRAS’ speed estimator which is more sensitive to its respective inductance parameter ‘ΔL’. Thus, making the proposed speed estimator better than Z-MRAS speed estimator in this respect. This estimator is also free from drift problems which are associated with pure integrator, as no integration related terms can be seen in both reference and adjustable models of the proposed scheme which is unlike the case of existing F-MRAS scheme which involves integrator in the adjustable model. Also, the proposed MRAS scheme is found to be stable in both motoring and regeneration modes which is concluded by performing the stability-analysis. Thus, making it suitable for aircraft propulsion applications. The sensorless-drive has been simulated in MATLAB/SIMULINK and verified experimentally on the dSPACE-1104 platform.
查看更多>>摘要：? 2022 Elsevier LtdMass standards are essential for the precise measurement of mass. Due to the increasing demand for small mass measurements, it is essential to be able to disseminate the sub-milligram mass standard from the National Metrology Institutes. Recently, the National Metrology Institute of Japan has developed an apparatus for mass calibration of sub-milligram weights by automatically transporting the weights. Consequently, the masses of the weights can be calibrated accurately and reliably. Sub-multiple calibration is often used for accurate mass calibration of weights smaller than 1 kg. In this study, by combining this method with the developed apparatus, the mass calibration uncertainty of sub-milligram weights was improved. The mass calibrations of 0.1 mg, 0.2 mg, and 0.5 mg weights were performed with standard uncertainties of 0.019 μg, 0.023 μg, and 0.040 μg, respectively. These uncertainties were smaller than the calibration uncertainties obtained by manually transporting sub-milligram weights to an ultra-micro balance.
查看更多>>摘要：? 2022 Elsevier LtdWe present multiple models for the problem of wind estimation by a multirotor drone in low altitude atmospheric turbulence. Data is collected by test flights with an instrumented drone in proximity to an anemometer for training, validation, and testing. Three machine-learning models are developed: a long–short-term-memory (LSTM) neural-network, an artificial neural-network, and a Gaussian-process-regression. These models are developed with variations in the inputs, considering the addition of drag estimations by known equations of motion and motor speeds, both of which improved performance. The LSTM model performed the best reaching 0.34 m/s root-mean-square-error in validation. The similarity between all model's performance without optimization indicates that we may be approaching the limits of accuracy of the experimental “ground truth”- a single anemometer that cannot be exactly co-located with the drone. The performance demonstrated so far suggests that the method may be useful in pollutant plume characterization, preliminary wind surveys, and other applications.
查看更多>>摘要：? 2022 Elsevier LtdData driven intelligent method for fault diagnosis has become a widely used technology. However, the traditional machine learning methods are limited when using two-order signal feature for modeling. When the two-order signal features are vectorized as the input, their structure information will be lost. To fully protect the structural information, a tensor-based classification method is proposed, termed adaptive maximal margin tensor machine (AMMTM). The core of AMMTM is to establish a pair of interactive hyperplanes, so that each type of samples bounds nearing its corresponding hyperplane and away from another hyperplane as far as possible. Meanwhile, a deviation parameter is introduced into the 2-norm distance metric, which changes the constraints on the hyperplanes and maximizes the distance between the two hyperplanes, so as to improve the generalization ability and robustness. Two roller bearing datasets are used for validation, and the experimental results show that AMMTM has superior classification ability.
查看更多>>摘要：Complete ground reaction forces (GRFs) are vital for biomechanical analysis. The GRFs are currently measured by force plates. The measurement of GRFs during stair walking is difficult due to the need for instrumented staircases. We trained two bi-lateral long short-term memory (BiLSTM) neural networks to estimate 3D GRFs during stair ascent and stair descent using the whole-body kinematics as the input. The dataset is collected from eighty subjects, including healthy and knee osteoarthritis individuals. We also developed a post-processing algorithm to remove artifacts on GRFs in the swing phase. Our models achieved excellent accuracy compared with the measured GRFs with the correlations of 0.908～0.991, the root mean squared error (RMSE) of 3.29% and 3.56% body weight (BW) and the normalized RMSE (nRMSE) lower than 5% and 8% for the complete GRFs during stair descent and ascent. Using our models, researchers can estimate 3D GRFs during stair walking without instrumented staircases.
查看更多>>摘要：? 2022 Elsevier LtdPlanetary gearset is a vital dynamic component in helicopter transmission. In the planetary gearbox, there are many nonlinear dynamic factors, such as time-varying meshing stiffness, bearing support stiffness, comprehensive transmission error and tooth backlash. These nonlinear factors will deeply affect the vibration response characteristics of the gearbox system, and bring new challenges to the crack fault detection and diagnosis. To unveil the nonlinear properties of planetary gear set, a 21 degrees of freedom translational-torsional model of the planetary gear set is established by integrating above-mentioned nonlinear factors. Analysis of the fault influence on natural frequency and statistical indicators of simulation responses, the optimal indicators for fault detection are found. Then, nonlinear dynamic characteristics of gear system under fault state are conducted, and crack fault symptoms are pointed out using time-domain waveform analysis and power spectrum analysis of response signals, which actively illustrates the system fault mechanism and achieves fault isolation. Finally, the effectiveness of the model for planetary gear set with tooth crack is verified by experiments.
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