查看更多>>摘要：This paper proposes an ultrasonic time-of-flight (ToF) based technique to estimate the relative humidity of the environment accurately. The framework of the proposed model is to let a fuzzy controller classify the input data to different segments based on the fuzzy output, and for each segment of data fed into a specific pre-trained neural network to predict the relative humidity. Neural networks are first trained, and the trained networks are used to estimate the relative humidity. The result shows that the proposed fuzzy-artificial neural network model gives better performance with an average root means square error (RMSE) of 1.269, mean absolute error (MAE) of 1.0415, mean absolute percentage error (MAPE) 1.962 and the coefficient of correlation (R-values) of 0.9468 compared to other methods. Experimental results indicate that the variation in relative humidity estimation is bounded by +/- 3% which is as good as commercially available off-the-shelf relative humidity sensors.
查看更多>>摘要：Adopting a more scientific and precise assessment method to evaluate the current running performance of coal mills in practice work is essential to maintain the security and reliability of the coal-fired power plant. However, traditional assessment methods have ignored an important problem that the importance among variables varies with the current operation data of coal mill, which has a serious influence on performance evaluation of coal mill. In this paper, a bran-new GA-IFCM-IDHGF assessment method is proposed. Genetic algorithm (GA) is first applied to optimize initial parameters, which is fundamental and significant step to obtain more accurate the number of clusters. Secondly, intuitionistic fuzzy clustering model (IFCM) is adopted to identify the running modes of the coal mill. According to the Delphi, analytic hierarchy process, gray relations analysis and fuzzy integrated evaluation (DHGF), the security range of variables under the normal observed samples from different running modes is acquired, which is helpful to determine whether the current operation data is normal data. Subsequently, an improved Delphi, analytic hierarchy process, gray relations analysis and fuzzy integrated evaluation (IDHGF) method is used to assess the current running performance of coal mill under the abnormal monitoring data. The performance of the proposed performance assessment method is verified through its application in a self-defined step fault system and an actual industrial cases of coal mill. Compared with the traditional methods, the experimental results demonstrate the effectiveness of the proposed method.
查看更多>>摘要：Vibratory gyroscopes are the most ideal novel inertial sensors in the 21st century. The amplitude is an important index of vibratory gyroscopes. The high-frequency disturbance is a common and intricate problem in vibratory gyroscopes. The paper investigates a novel tracking control approach that tracks the reference amplitude signal and suppresses the high-frequency disturbance for vibratory gyroscopes. First, the original dynamic system is transformed into an interval type-2 (IT2) fuzzy system such that the nonlinearity and uncertainty of the system are well handled. To reduce the conservatism of the asymptotic stability condition, a novel coupling-factors-dependent Lyapunov function is constructed, in which the system state depends on coupling factors. Then, to track the reference amplitude signal and suppress the high-frequency disturbance simultaneously, a doubly-fed tracking controller with nonfragile property is developed such that the state error system is asymptotically stable with a prescriptive performance. Finally, the comparative results of a vibratory gyroscope are done to show that the proposed control approach can greatly improve the control precision of amplitude signals, which demonstrates the effectiveness of the proposed control approach.
查看更多>>摘要：Driving speed is one of the key concepts and risk factors in transportation research. The insights into operational and safety aspects of driving can be provided by floating car data (FCD), collecting information about speed, position and time by vehicles themselves. FCD are often recorded at high frequency, representing a continuous phenomenon. As such, convenient approach can be functional data analysis (FDA). Speed trajectories are investigated, identifying sections with rapid changes of speed and sections where drives in central and auxiliary lanes cannot be distinguished in terms of their speed. The effect of curvature and auxiliary lanes on driving speed was shown by functional regression models. Significant influence of road shape on speed was found for ramps with complex shape. The accuracy of regression models was assessed by RMSE, NRMSE, and precision of estimators by point-wise confidence intervals. The analysis was performed on an expressway interchange in Brno, Czech Republic.
查看更多>>摘要：Strap-down inertial navigation system (SINS) and celestial navigation system (CNS) integrated navigation have been widely applied in ships, aircraft and spacecraft etc. However, in practice, its performance is highly depending on the horizon reference accuracy, which is usually difficult to guarantee. In this work, we propose a SINS/CNS integrated navigation scheme based on a novel mathematical horizon reference (MHR) determination method. More specifically, inertial coordinate system is used in constructing the MHR, where the attitude and position errors could be decoupled and compensated, respectively. Then, a more accurate MHR could be established, thus resulting in better navigation results. Comparative numerical simulations for a maneuvering flight have been conducted, and it is shown the proposed approach has the best converging speed as well as the highest navigation precision compared with SINS and existing MHR-based SINS/CNS schemes, and all-state optimal estimation could be achieved, thus enabling fully autonomous and high-precision navigation.
查看更多>>摘要：The article presents a new version of the method for estimating parameters in a split functional model, which enables the determination of displacements of geodetic network points with constrained datum. The main aim of the study is to present theoretical foundations of M-split(CD) estimation and its basic properties and possible applications. Particular attention was paid to the efficacy of the method in the context of geodetic network deformation analysis and to the robustness properties of the proposed method. The theoretical considerations were verified by means of two computational tests conducted using the Monte Carlo simulation. The obtained results of methods of estimation parameters in a split functional model were compared with the results of classical method of the least squares estimation. The numerical examples provided in the study indicate the basis properties of M-split(q)(CD) estimators being determined.
查看更多>>摘要：Background: With the rapid development of information technology and the further popularization of the Internet, various industries in the whole society rely more and more on information. The network album system is one of the products in the information age. Purpose: This paper analyzes and studies the role of album service in image resource construction based on wireless network environment, and aims to reveal the optimization of image resource construction in this process through the research on image storage, acquisition, browsing and sharing of "small direction" network album. Method: This research mainly focuses on two aspects: the analysis and acquisition of data, the service carrier of network album - photo and image resource structure. Firstly, define the construction standard of the network album system, and analyze the specific performance requirements and non functional requirements of the network album system. In terms of system architecture, multi server architecture is adopted to realize basic load balancing and improve system performance. The comparison before and after system application is carried out in combination with image spatial resolution, image spectrum and image characteristics, so as to highlight the role of album service in wireless network environment. Results: The experimental results show that the highest value of the detection spectrum can reach 0.912. In the process of image browsing, the image spatial resolution has been greatly improved under the construction of wireless network environment. Among the 20 images in the experiment, the highest is 7.89.
查看更多>>摘要：Internal leakage is one of the most common faults in hydraulic cylinders, and seal wear is the main factor in internal leakage. However, it is difficult to detect seal wear and internal leakage in hydraulic cylinder using present approaches due to the complex hydraulic system. Therefore, an intelligent fault diagnosis method based energy features fusion is proposed to detect seal wear and internal leakage. First, computational fluid dynamics (CFD) technology was adopted to analyze the flow field in the internal leakage area of hydraulic cylinder, and it was found that energy features of pressure signal are related to internal leakage. Then, wavelet packet transform is applied to extract energy features of pressure signal. Finally, energy features is decomposed into statistics by multivariate statistics theory. Statistics are used to detect piston seal wear and internal leakage. The proposed method creatively studies seal wear and internal leakage from the perspective of flow field analysis, which does not require a large number of fault samples and complicated parameters optimization. Experimental in-vestigations are performed to validate the performance of the proposed approach. It is shown that the proposed method has much more robustness and accuracy than several classical fault diagnosis methods. The study does provide an effective way to detect seal wear and internal leakage in hydraulic cylinder.
查看更多>>摘要：Split-core current transformer (CT) has been widely used in low-voltage distribution networks due to the merit of live-line installation. However, as the air gaps of the iron core exist, there is a possibly varying magnetizing error, which will severely degrade the accuracy of split-core CT, caused by manual installation deviation, vibration, and temperature variation in field operation. To tackle this issue, this paper proposes an online self-correction method to improve the measurement accuracy of split-core CT. The proposed method contains (1) an auxiliary winding loop (AWL) added to the split-core CT, to temporarily and intermittently operate in on/off modes; and (2) a self-correction algorithm (SCA) based on the operation of the AWL, to online determine the varying errors and then to give corrected measurement results. Moreover, a low-cost solution for embedding the proposed method in multiple split-core CTs in low-voltage distribution network is provided via series-connecting the AWLs. For validation, a prototype embedded with the proposed method is implemented, and is tested versus different applied primary currents and burdens. The test results exhibit that the proposed method effectively improves the measurement accuracy to a high class (0.2). Also, the proposed method's robustness to varying gap lengths and temperatures is verified. Notably, even under the extreme condition with a 0.520 mm gap, the measurement errors are reduced from the inherent values up to 30.9% and 648 mrad to a satisfactory range below 0.195% and 0.295 mrad, respectively.
查看更多>>摘要：Accurate measurement of correlated color temperature (CCT) which represents the color of light source is critical in photometry research. Current research shows that the value of CCT in environment has diverse and important effects on human perception and behaviour. Since we spend a large portion of our day indoors, these effects have a considerably greater impact on our daily lives than we think. For instance, the temperature perception of the environment or shape perceptions of students is related to CCT value in the environment. The value of CCT which is created by light sources in environment can be determined in a variety of ways in literature. CCT values of the environment can be measured precisely with spectroradiometers, which are special and relatively expensive measurement devices that aim to precisely measure radiance, luminance and chromaticity of light. Additionally, CCT values can be estimated with lower accuracy using various color space transformations and predefined models instead of spectroradiometer devices. In this study, an alternative approach to these two techniques for measuring CCT in the environment is proposed. CCT values of the environments were determined closer to spectroradiometer measurement results thanks to the deep regression model developed within the scope of this study using only RGB cameras. 191 different specially created RGB images and corresponding CCT values were taught to deep learning network structure for creating a regression model. The proposed approach performance was compared to alternative CCT calculation methods in literature using a variety of real-scene test images.
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Elsevier