查看更多>>摘要：? 2022Due to the extreme temperature with significant variation in the alpine region, the tunnels in this area are subjected to intense freeze–thaw cycles and frost heaves, which leads to the cracking of the second lining structure. We propose an approach to monitor the frost heaving strain of the second lining and simultaneously measure the thermal strain and applied stress strain of the structure. The Fiber Bragg Grating (FBG) strain sensors are installed on the structure surface to measure the strains caused by the thermal strain and loaded stress. Meanwhile, one FBG temperature sensor is installed on the structure surface to measure the local temperature. Then, the structure thermal strain and applied stress strain are simultaneously measured based on the sensitivity difference for temperature and strain response of the above two measurement methods. The proposed approach is implemented in an alpine region tunnel. The results show that the local temperature is inversely proportional to the total strain and the thermal apparent strain of the second lining. The applied stress–strain of the lining fluctuates in a small range, and the thermal strain from the daily temperature difference incremental demodulation is very close to the daily strain difference. Therefore, the main cause of lining frost damage is the thermal strain due to the local temperature variation, and there is no frost heave occurred in the surrounding rock. Thus, the method is offered to monitor the freeze–thaw cycles and freeze-swelling effects in the extreme cold and high-altitude tunnels.
查看更多>>摘要：? 2022Pressure-sensitive paints using poly[1-(trimethylsilyl)-1-propyne] (PTMSP) as a binder polymer are capable of capturing subtle pressure fluctuations under low-pressure conditions, but the pressure sensitivity is unstable. The dependence of the pressure sensitivity stability on environmental factors and coating parameters was evaluated under low-pressure conditions. The pressure sensitivity decreased from 56.3 to 42.5%/kPa at an extremely low pressure after 60 min, and the stability decreased significantly as the background pressure was reduced. An apparent change in the pressure sensitivities and stability was observed from 278 to 318 K, with optimal performance being obtained at 298 K. A comparison of the pressure sensitivities and emission intensities of shaded and irradiated samples stored at low pressures indicated that the excitation light hardly aged the binders. The pressure sensitivity stability decreased as the luminophore concentration increased, while an increased in the paint thickness improved both the pressure sensitivity and stability.
查看更多>>摘要：? 2022 Elsevier LtdThe premise of identifying, locating, and sorting coal and gangue using photoelectric sorting technology is that independent image targets should be obtained. In this study, concave point detection and segmentation algorithm are proposed to segment overlapping particles. First, the edge coordinate sequence is obtained for the overlapping part of the concave defect area of the adhesion target and the binary image of the adhesion target. Subsequently, the initial linear equation passing through the beginning and ending points of the sequence is built. The traversal sequence updates the new linear equation parallel to the initial linear equation, and the positional relationship between the front and back points of the search point and the linear equation is determined. The concave point detection is transformed into the positional relationship between pixels and linear equations. Lastly, the segmentation line segmentation image is generated based on concave points, and the segmentation accuracy reaches 93.15%.
查看更多>>摘要：? 2022 Elsevier LtdOne of the main concerns of battery management systems is predicting the degradation of lithium-ion batteries, which remaining useful life prediction is an essential tool for prognostic and health management of batteries. In this study, we develop a novel prognostic architecture that is based on a least-squares generative adversarial network with the gated recurrent unit as the generator and multi-layer perceptron as the discriminator and use it to predict the Lithium-ion batteries’ remaining useful life. The proposed method aims to learn the probability distribution of future values in an adversarial training fashion. This generative adversarial network gives more penalties to large errors and addresses the vanishing gradient problem during training. As a result, the predicted values will get closer to the actual data. Furthermore, to obtain high prediction accuracy, time-domain features are evaluated using statistical formulas. The most important features are then selected using the random forest algorithm and fed to the network as a multivariate input set. The performances of the proposed method are tested using a battery degradation dataset from the data repository of Prognostics Center of Excellence at NASA. Furthermore, experimental data from lithium-ion cells at different current rates are conducted for evaluation and verification. The obtained outcomes demonstrate that the designed model achieves the low prediction error of 2.63% and maximum absolute error of 0.02.
Nur Ashakirin S.Aniq Shazni M. Haniff M.Farhanulhakim M. Razipwee M.Mahmoudi E....
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查看更多>>摘要：? 2022 Elsevier LtdThe determination and evaluation of urea levels aid in the diagnosis of kidney diseases. Herein, we report a label-free detection scheme based on silver reduce graphene oxide (AgrGO) modified working electrode (SPCE) is employed as solid support for the immobilization of urease (Urs) for detection of urea. The modified SPCE is fabricated on electrochemically deposited AgrGO shows excellent urea detection at a wide linear range of 0.001–10 mM, and the detection limit of 0.1623 μM and sensitivity of 47.598 μAμM?1cm?2. The sensor was found to be highly selective for urea without any response interferents. Moreover, the applicability studies were successfully evaluated by artificial urine with good stability and reproducibility.
查看更多>>摘要：? 2022Measurement uncertainty is as important as measurement in metrology and industry. The GUM and its supplements provide a widely accepted framework for evaluating measurement uncertainty; but don't provide a reasonable assessment method for some special circumstances, especially for dynamic measurement. Several emerging methodologies with different mathematical approaches are used for evaluating the dynamic uncertainty in a specific application, such as knowing the characteristics of data. To expand the applicability, a self-adaptive method is proposed. This method evaluates measurement uncertainty by analyzing the compositions of dynamic data, regardless of linearity, stationarity, or stochasticity. Information entropy on spectra combined with EDM algorithms is presented to divide dynamic data into deterministic and stochastic components; and then a Bayesian model and a time-varying auto-regression model are used to analyze decomposed components, respectively. Synthetic noisy signals and experimental data from a double-rotor table are utilized to demonstrate the effectiveness of the proposed method.
查看更多>>摘要：? 2022 Elsevier LtdVision-based technique for fill level measurement in pelletization is widely used in industries and is crucial to ensure high-quality production. However, the existing approaches are 2D-vision-based and majorly designed for rotary drums. Nevertheless, for disc pelletizers, it remains an under-study and challenging problem due to the complex structure of apparatus and granules kinetics in disc. In this work, an online fill level measurement method for disc pelletizers by an RGB-D camera is proposed. Firstly, a background depth data subtraction and automatic granular area identification method are developed to obtain the 3D pointe cloud data of the granular area by machine learning and model-based processes; thereafter, a proportion conversion algorithm is developed to real-time calculate the granular pile volume and fill level. Extensive experiments demonstrate the effectiveness of our approach with an average relative error of 5.42%, which meets the requirements in industries.
查看更多>>摘要：? 2022 Elsevier LtdThe aim of this paper is to demonstrate the exploitability of Long Range Wide Area Network (LoRaWAN) networking to set up a wireless transmission channel allowing the real time data collection from underwater depths up to more than 1 m. To this aim, a theoretical analysis is carried out to determine the actual feasibility of this link taking into account the technical features of the LoRa channel. Following this analysis, field tests in a swimming pool have been performed analyzing the transmission performance in terms of Received Signal Strength Indicator (RSSI) and Signal to Noise Ratio (SNR) for different transmission parameters and at increasing depths. Moreover, two test campaigns varying the antenna's sensor node and the packet payload length have been performed. Experimental results have seen a good corroboration of the theoretical analysis with efficient underwater LoRaWAN data transmission at depths up to 110 ±5 cm, considering 14 dBm transmitted power.
查看更多>>摘要：? 2022 Elsevier LtdThis article proposes a robust and enhanced three-phase fundamental frequency estimation algorithm for the electric aircraft grid. Unlike conventional frequency-locked loops, the digital signal processing technique-based frequency estimator proposed relies on the storage of five consecutive samples of the fundamental grid voltage signal. Furthermore, the ability to successfully operate at a low sampling frequency, i.e. 8 kHz, makes it sufficiently attractive as regards reducing the memory storage in a low-cost real-time controller. The proposed frequency estimator can additionally eliminate the negative effects of the DC-offset and the fundamental negative sequence components present in the grid signal without any additional effort. Also, the tuning efforts are reduced for the frequency variation range of 350–900 Hz owing to the existence of a single tuning gain parameter. The proposed algorithm has also been found to have a fast dynamic response, which has been experimentally validated through the use of a real-time digital controller.
查看更多>>摘要：? 2022 Elsevier LtdThis paper presents an experimental investigation of rotating source localization to identify the axial fan noise with high spatial resolution methods. It exploits the on time-domain de-Doppler, and sparsity-based inversion and the convolution model to approximate the power propagation model of the rotating source. This work is also an extension of the previous paper of authors. But the focus of this study is the experimental investigation and application of actual data. To evaluate the performance of the proposed algorithm, a vortex generator is attached to the fan blade, creating discontinuities in the blade to simulate axial fan blade defects (cracks, holes, dust accumulations, etc.). The experimental data are shared as a data benchmark to promote further studies in the field of rotating acoustic localization. Compared with the state-of-the-art rotating Beamforming method (ROSI), the acoustic imaging results at various working frequencies for three different axial fans with different rotating speeds (RPM) are accurately identified and sparsely distributed. In addition, the power propagation model derived in the previous paper can be interpreted by a convolutional approximation model in this paper, and this technique can help to reduce the computational costs of proposed methods for real applications. The accuracy of the aerodynamic noise positions estimated by the proposed method are further proved to match well with the aerodynamic mechanism.
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