查看更多>>摘要：? 2022 Elsevier LtdThe transient electromagnetic method (TEM) is used to detect mineral resources and mined-out areas, to eliminate the secondary field signal noise interference, this paper proposes an algorithm for denoising the TEM signal based on Variational Mode Decomposition (VMD) and Wavelet Threshold Denoising (WTD) methods. The Grey Wolf Optimization (GWO) algorithm solves the parameter combination (K, α) in the VMD, and the K intrinsic mode functions (IMFs) are then obtained using the decomposed TEM signal. Subsequently, all IMFs are analyzed according to the correlation coefficient and divided into signal modes, mixed modes, and invalid modes. Finally, the mixed modes are denoised by WTD, the signal and denoised modes are combined. To validate the effectiveness of the VMD-WTD algorithm, the method was compared in simulations with the Ensemble Empirical Mode Decomposition (EEMD) algorithm and various other methods previously developed to improve the TEM, its performance in a field experiment was also confirmed.
查看更多>>摘要：? 2022 Elsevier LtdInduction motors are widely used in our daily life and industrial machines. Single-phase induction motors with small power, manufactured with few horsepowers (HP), are preferred as compressor motors for household refrigerators and air conditioners. This inevitably leads to the lower energy consumption of compressor systems and requirements for a more compact design. In this study, a single-phase induction motor manufactured with classical core material for a certain power value is modeled using finite element analysis (FEA) software and the power losses are investigated. Later, this electric motor is designed with 6.5% SiFe jfe super core material, one of the soft magnetic core materials, for the same power value and comparative performance studies are performed. In these comparisons, mechanical volume and weight for the motor dimensions, electrical power losses and electromagnetic parameters are studied. It is therefore recommended that the jfe super core material, which has become popular in recent years, be used for the manufacture of single-phase induction motors, which are often used in household appliances.
查看更多>>摘要：? 2022 Elsevier LtdThe fast and precise positioning measurement of nuclear fuel rod element are an important part of the nuclear fuel rod bundle production line. This paper develops a new positioning measurement imaging device and proposes a positioning measurement algorithm based on spacer retrieval network. Firstly, the spacers retrieval network is trained to obtain the spacer's types and location information, and statistically realize the type determination and initial positioning measurement of the nuclear fuel rod. Then, using the a priori information from the initial positioning, we intercept the regions of interest (ROI) of the spacers and perform contour extraction to achieve the precise positioning measurement of the nuclear fuel rod. The experimental results show that the equipment achieves 0.035° positioning measurement accuracy, and the positioning beat reaches 4.234 s/rod. The efficiency and accuracy of the proposed positioning equipment meet the application requirements of nuclear fuel rod bundle production line.
查看更多>>摘要：? 2022 Elsevier LtdThe assembly performance of hemispherical resonant gyroscope (HRG) is directly affected by the spatial pose of the resonator and the electrode carrier, which can be reflected in the capacitance uniformity. This paper proposed a fast identification algorithm for pose error based on HRG assembly capacitance uniformity. A forward mathematical model for calculating capacitance from the resonator's pose was established and verified by experiments and simulations. The effect of pose on the capacitance was analyzed by using the mathematical model. Based on the data of pose and capacitance obtained from the mathematical model, the capacitance-pose inverse model was constructed by back propagation (BP) neural network. This novel algorithm provides a swift way to identify the pose error of resonator and achieves capacitance uniformity in HRG assembly, which can significantly improve the assembly quality and efficiency of HRG.
查看更多>>摘要：? 2022Magnetic particle testing (MPT) has high sensitivity, which is popular in ferromagnetic material detection. However, results of MPT always mix with fake magnetic particle indication (FMPI) and point noise caused by nonrelevant magnetic particles. It mainly depends on manual work to find defects in MPT. In this paper, Hough Transform, which is robust to the point noise, is introduced to automatically identify the linear features of magnetic particle indication (MPI) caused by defects. However, the algorithm cannot distinguish between the similarly shaped FMPI and MPI. To address the problem, we proposed a digital model aided de-noising Method. Specifically, the density of normal component of magnetic flux on specimen surface is calculated by finite element analysis to evaluate the possibilities of FMPI occurrence. Then detection results are compared with the calculation to eliminate FMPI. Experiments show that scratches on hub bearing can be successfully identified by the proposed method.
查看更多>>摘要：? 2022 Elsevier LtdThe spherical target is critical in many terrestrial laser scanning applications. Accurately and robustly estimating its geometric center based on a point cloud is a problem of widespread concern. To address this problem, we propose a novel adaptive grid search (AGS) algorithm, which makes full use of the point cloud and geometric feature of the spherical target, and obtains the optimal fitting parameters through a finite number of iterative optimizations. Firstly, we utilize the centroid of the point cloud and the estimated radius of the spherical target as constraints to establish an initial constraint space. Secondly, we use grid search to determine the initial optimal solution of the parameters. Finally, we iteratively update the constraint space and the optimal solution utilizing the previous optimal solution and the parameters scales, and take the solution with the least error metric as the final optimal solution. We have validated the feasibility and reliability of the algorithm with actual data and simulated data, respectively, and compared the fitting results with those of the Non-Least Squares algorithm (NLS) and the M?estimator SAmple Consensus (MSAC) algorithm. The experimental results show that the AGS algorithm can achieve high-precision fitting of various point clouds of spherical targets and overcome the defects of the other two algorithms that are easily affected by noise and coverage. Due to iterative optimization, the running time of the AGS algorithm is slightly longer than the other two algorithms, but it can usually complete the fitting within 5 s.
查看更多>>摘要：? 2022 Elsevier LtdMultipath effect is one crucial impact on the performance of wireless communication systems. Multipath measurement has attracted more attention. While in the multipath measurement system, the band-limited issue causes chip distortion and brings errors in results. This paper proposed a chip distortion error post-processing method for multipath estimation algorithm. First, the method uses the dynamic performance index of system response, to analyze the effect of overshoot on the distortion of the correlation function and deduce three parameters. Second, the method uses the three parameters to correct estimation errors. Finally, the proposed method is tested in simulated and practical environment. For simulated experiments, Wasserstein distance is adopted as the evaluation index. We construct the multipath measurement system for practical experiments to obtain the main paths and measurement error. The statistical results show that the proposed post-processing method is useful in alleviating estimation errors caused by band-limited issues.
查看更多>>摘要：? 2022 Elsevier LtdOn complex batch industrial processes, soft sensor modeling plays a key role in process control and monitoring. Considering the nonlinearity, time-varying, and repetitive nature of the batch process, this paper proposes a soft sensor modeling method (VMD-SEAE-TL) based on variational mode decomposition (VMD), stacked enhanced autoencoder (SEAE) and transfer learning (TL) algorithms for online detection of key variables in batch industrial production processes. Firstly, the raw industrial process data are decomposed and reconstructed using VMD to achieve denoising and reduce the non-smooth characteristics of the data series. Secondly, based on the reconstructed process data, the SEAE network is used to deeply extract data feature information and achieve high accuracy regression prediction. Here, during the SEAE training process, each layer of the enhanced autoencoder (EAE) network reconstructs both the network input and the original input. The purpose of this operation is to extract the deep feature information of the process data and to ensure that there is no cumulative loss of the original input information. Further, it is considered that the working conditions in the batch industrial production process are time-varying, and this often makes it difficult for the model trained on the source domain data to accurately predict the trend of the process variables in the target domain. For this problem, the maximum mean deviation (MMD)-based transfer learning algorithm is introduced, which is used to solve the domain adaption problem with changing working conditions. Finally, based on two actual industrial process cases, the effectiveness and practicality of the proposed soft sensor are verified by various experimental results.
查看更多>>摘要：? 2022 Elsevier LtdInertial measurement unit (IMU) systems are offering promising alternatives to optoelectronic systems for measuring human movement. The objective of this study was to assess the validity of a new inertial measurement system, iSen STT-IWS sensors, with reference to the optoelectronic motion capture system OptiTrack. 22 young participants performed three minutes of treadmill walking at different speeds. Hip, knee and ankle joint angles in the sagittal plane were compared between the two systems. Accuracy and repeatability of iSen IMU measures was evaluated with the Root Mean Square Deviation (RMSD) and Lin's Concordance Correlation (LCC). A good to tolerable Isen measures’ accuracy was found (RMSD < 10°, LCC > 0.75) and reliability decreased with walking speed. Results indicated excellent test–retest repeatability of the inertial system (Intraclass correlation (ICC) > 0.75). Sagittal kinematic gait estimation using the iSen IMU system can be reliably used for clinical purposes on older adults.
查看更多>>摘要：? 2022 Elsevier LtdThe bidirectional flow of electrical power has mandated the monitoring of the distribution system (DS) in real-time using synchronized data to overcome problems linked to grid stability, that can cause cascade failure. This synchronized data is gathered by micro-phasor measurement units (μPMUs) and is beneficial in determining the operational health of the DS. In the present article, a multi-objective optimal μPMU placement problem (μPPP) for DS is addressed for two conflicting objectives viz., minimization of μPMU installation cost and maximization of measurement redundancy using non-dominated sorting genetic algorithm-II (NSGA-II) and multi criteria technique called PROMETHEE-II under practical DS scenarios. The proposed solution methodology is compared with well-established Multiobjective techniques and validated on Indian 85-bus and standard IEEE distribution systems, to establish its superiority in locating Pareto optimal solutions (single/multiple solutions). Finally, cost analysis is done which indicates substantial cost saving when μPMUs with variable cost are considered.
NSTL
Elsevier