查看更多>>摘要：? 2022 Elsevier LtdThe geomagnetic field vector information is critical to the navigation and positioning in the magnetic measurement of satellites, ships, and aircraft, however, suffers from the internal inherent error and the internal error interfering magnetic fields. Most real-time geomagnetic correction algorithms based on the specific ellipsoid fitting typically lead to the difficulty in real-time acquisition of the attitude roll angle of the projectile and the estimation accuracy. Herein, we propose a novel real-time estimation algorithm based on Magnetometer measurement involved two-step adaptive Kalman filter. The first-step adaptive Kalman filter algorithm is proposed for online error compensation of the magnetometer by using the error model and ellipsoid model of the magnetometer. The robust estimation theory is proposed to apply to the first-step adaptive Kalman filtering for ellipsoid fitting. The capability of preprocessing data and the adaptive observation vector's covariance matrix enable the real-time separation and correction of outliers. In addition, a vector-dot product invariant method is proposed to estimate the 12 coefficients in the magnetometer error model, solving the problem that the traditional method cannot ultimately determine the coefficients of the error matrix. Furthermore, the second-step adaptive Kalman is utilized to adaptively real-time estimate the roll angle. In particular, the results of the simulations and experiments show that the algorithm's parameters tend to be stable, beginning since 3 s for the data collection; and the accuracy range of the roll angle is boost to between ±0.4°. Moreover, the error parameters of the magnetometer are fully calibrated, and the estimation accuracy of roll angle is improved by 1/2 with regard to that of conventional methods. The results demonstrate the capability of compensating for the random magnetic field error caused by the motor. The results show that the two-step adaptive Kalman filter algorithm can reduce the estimation error of roll angle and could be extended to practical engineering applications.
查看更多>>摘要：The goal of this study is to verify whether the low-cost GNSS receivers may provide the tropospheric parameters with accuracy close to that of high-grade ones. In this way, we address a scientific question on the potential usability of low-cost receivers for climate monitoring. We assess zenith tropospheric delays (ZTD) and, for the first time, horizontal gradients derived from Precise Point Positioning with low-cost receivers. ZTD estimates are also validated against ERA5, which is the fifth generation reanalysis for the global climate and weather produced by the European Centre for Medium-Range Weather Forecasts. We proved that low-cost equipment has the potential to provide tropospheric estimates with comparable accuracy to high-grade receivers. We also reveal a high agreement between GNSS ZTDs and these of ERA5 reanalysis. Finally, we show that applying a surveying-grade antenna to a low-cost receiver may enhance the accuracy of the tropospheric estimates derived from mass-market receivers.
查看更多>>摘要：? 2022 Elsevier LtdTraditional methods for inspecting impellers on a three-axis Coordinate Measuring Machine (CMM) lack efficiency, since they need to adjust the clamping posture of the impeller or the probe orientation many times to avoid interference. In this paper, we propose an algorithm to generate efficient and interference-free scanning path for inspecting impeller on a cylindrical CMM. Firstly, the minimal number of probe tilt angles for inspecting the blade section is formulated as an optimization problem. The blade section is divided into several paths, each of which corresponds to one of the optimized probe tilt angles. Then, the feasible turntable rotation angles (FTRAs) in each path are calculated by an efficient incremental algorithm. Finally, the B-spline fitting and bisection method are used to generate a smooth turntable trajectory under the constraints of FTRAs. Inspection experiments on two impellers verify the efficiency of the proposed algorithm and the smoothness of the turntable rotation.
查看更多>>摘要：? 2022 Elsevier LtdAt present, numerous deep learning techniques are being used in fault diagnosis with good effects. However, obtaining a sample of a fault may be difficult in certain circumstances. Moreover, the distribution of the sample is highly unbalanced. Typically, when the sample size is unbalanced, deep learning methods exhibit the phenomenon of overfitting, which results in a lack of generalizability and precision. In this paper, we proposed an adaptive sparse contractive auto-encoder (ASCAE) and an improved gray wolf optimization unsupervised extreme learning machine (IGWO-USELM) model for diagnosing unbalanced rolling bearing faults. First, CAE was improved by employing sparse graph embedding. Additionally, homotopy regularization was utilized to optimize sparse coefficients. Consequently, the effect of fault feature extraction was improved. The IGWO model was improved using Tent chaotic mapping to compensate for the fault sample's sparse information. Subsequently, we used the IGWO to dynamically optimize USELM's performance. Accordingly, the IGWO-USELM model was developed. The ASCAE was used to extract multi-layer features from the vibration signal. Additionally, the extracted features were fed into the IGWO-USELM fault diagnosis model. Lastly, we performed experimental analysis on the fault dataset from Case Western Reserve University and the two real datasets. The results demonstrate that our method is capable of extracting time–frequency features of high faults. The proposed method is the most accurate when the fault samples are unbalanced. It has demonstrated excellent performance, particularly on the real-world fault dataset. When noise is present, the proposed method exhibits excellent noise immunity and a short run time. A further advantage is that it can be used to perform real-time bearing fault diagnosis.
查看更多>>摘要：? 2022 Elsevier LtdThe main objective of this review is to facilitate a deeper understanding of thermal inertia principles and to analyze its impacts on the evaluation of reaction kinetics. At first, the physical meaning of thermal inertia is explained and discussed, and its significance is documented on numerous practical examples. An overview of methods dealing with thermal inertia by means of quantification and elimination of its effects is presented afterwards. The particular approaches are analyzed in detail and their advantages, disadvantages, limitations, and a potential field of applications are outlined. The comprehensive analysis of thermal-inertia related problems shows it as an omnipresent factor with an indisputable impact on thermoanalytical results, the reaction kinetics in particular. In this light, the fundamental question on the thermal inertia neglecting issue should be revised, since it is no longer actual to ask “if”, but definitely only “when” can it be neglected.
查看更多>>摘要：? 2022 Elsevier LtdThis paper presents the capabilities of an optoelectronic system to measure values describing the hydrodynamics of a two-phase downward flow in vertical pipes of a highly viscous liquid and gas. Common image processing methods used in the literature are unsuitable for the analysis of two-phase flow with particularly complex flow patterns. The designed and constructed measuring system and the appropriate selection of working media allowed measurements of a number of quantities characteristic for the gas–liquid flow falling in vertical pipes. The methodology of conducting measurements and their results as well as the analyses of selected quantities characterizing the two-phase flow are presented. The nature and form of the occurring waves are characterized. Experimental data are more accurate than those obtained with methods described in the literature. A camera placed in the flow channel limits the measurement to vertical downward flow only.
查看更多>>摘要：? 2022 Elsevier LtdMeasurement of temperature distribution is vital in boilers, heat exchangers, and other industrial applications. Acoustic pyrometry offers the advantage of measuring the temperature in the entire domain in a non-intrusive manner. Acoustic pyrometry involves estimating the temperature of the domain using the time of flight information between the transceivers. Since acoustic pyrometry is an inverse problem, it is sensitive to noise and the number of cells in the domain. Regularization methods help in obtaining feasible solutions. Therefore, the performance of four regularization methods, namely, Tikhonov, modified Tikhonov, Total variation (TV), and iterative reweighted least-squares (IRLS) in reconstructing three different temperature profiles, is studied and compared against the pseudo-inverse method. The effect of noise and the cell ratio (CR) on temperature reconstruction is also studied. Overall, the best results are observed for the coarsest cell ratio and modified Tikhonov with sharp filter regularization.
查看更多>>摘要：? 2022Compared with inner solid structures, the inner hollow structures of turbine blades show excellent mechanical properties and better physical properties, e.g., excellent heat dissipation and diversion effects, and light weight. Its complex inner structures cannot be detected accurately by traditional testing methods. Among all non-destructive testing (NDT) methods, ultrasonic testing method has certain advantages in measurement accuracy and efficiency for measuring wall thickness values. The accuracy of measurement results is provided by four criteria: precision, accuracy, stability, and efficiency. However, ultrasonic testing method still faces new challenges that are barely explored, e.g., inner structures have unique characteristics of complex geometrical features, the measurement process need to meet high-precision positioning and quickly detecting requirements. In this paper, in order to improve the detection accuracy and efficiency, an industrial robot is used to substitute the existing detection methods: once a new blade is clamped by terminal mechanism, a new calibration method adopted the six-point positioning scheme was provided to solve the problem of rapid and accurate updating tool coordinate system. The support vector machine (SVM) system was used to output regression results of the adjustment parameters based on the geometric features of distorted wave shapes. Two kinds of measurement paths were used to measure the wall thickness values for accurate measurement. The experimental results show the superiority and effectiveness of our method in terms of measuring stability, accuracy and testing efficiency.
查看更多>>摘要：? 2022 Elsevier LtdThe failure of glass fiber reinforced polymers (GFRP)–ultra-high performance concrete (UHPC) hybrid beams originate from its mechanical mechanism transition, which is reflected in the plastic deformation of its components. The plastic deformation could be sensitively detected using acoustic emission (AE) technique. In this study, AE technique was utilized to monitor the mechanical mechanism transition of the GFRP–UHPC hybrid beam through the push-out test of a bolted shear connection specimen. Results showed that AE parameters could reflect the damage transition of the push-out specimen from qualitative and quantitative perspectives. First, the variation characteristics of AE hits, energy, and ringing counts were remarkably discernible in the three loading stages of the specimen. And the plastic deformation of high-strength bolts could be identified by the increase in AE signals with high peak frequencies. Besides, the mechanical mechanism transition of the specimen could be distinguished by the intensive degrees transition of b-value points in the different loading stages. Finally, the boundary values of the historic index [H(t)] and severity (Sr) were proposed to quantitatively evaluate the damage degree of the specimen. AE technique provides a possibility of safety warning for the GFRP–UHPC hybrid beams because of its ability to effectively identify the mechanical mechanism transition.
查看更多>>摘要：? 2022 Elsevier LtdThis article aims to address some challenges in data-based damage localization by proposing innovative methods including a hybrid algorithm for feature extraction, a symmetric information measure for feature classification, and a probabilistic approach to threshold estimation. The hybrid feature extraction combines an autoregressive (AR) model with a novel non-parametric estimator of probability density function (PDF) under empirical data analysis. The great novelty of this method is to propose a new probabilistic feature as an empirical PDF of the AR coefficients. The proposed information measure is a symmetric divergence aiming at addressing the main limitation of the classical Kullback-Leibler divergence regarding its non-symmetric characteristic. Finally, the proposed probabilistic approach exploits the concept of Markov Chain Monte Carlo to estimate a trustworthy threshold for locating damage. Vibration responses of two civil structures are used to verify the proposed methods with several comparisons. Results confirm that the methods are successful in identifying damage.
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