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An Interpretable Bearing Fault Diagnosis Model Based on Hierarchical Belief Rule Base

  • Boying Zhao;Yuanyuan Qu;Mengliang Mu;Bing Xu;Wei He
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.5
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    • pp.1186-1207
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    • 2024
  • Bearings are one of the main components of mechanical equipment and one of the primary components prone to faults. Therefore, conducting fault diagnosis on bearings is a key issue in mechanical equipment research. Belief rule base (BRB) is essentially an expert system that effectively integrates qualitative and quantitative information, demonstrating excellent performance in fault diagnosis. However, class imbalance often occurs in the diagnosis task, which poses challenges to the diagnosis. Models with interpretability can enhance decision-makers' trust in the output results. However, the randomness in the optimization process can undermine interpretability, thereby reducing the level of trustworthiness in the results. Therefore, a hierarchical BRB model based on extreme gradient boosting (XGBoost) feature selection with interpretability (HFS-IBRB) is proposed in this paper. Utilizing a main BRB alongside multiple sub-BRBs allows for the conversion of a multi-classification challenge into several distinct binary classification tasks, thereby leading to enhanced accuracy. By incorporating interpretability constraints into the model, interpretability is effectively ensured. Finally, the case study of the actual dataset of bearing fault diagnosis demonstrates the ability of the HFS-IBRB model to perform accurate and interpretable diagnosis.

Zoning Permanent Basic Farmland Based on Artificial Immune System coupling with spatial constraints

  • Hua, Wang;Mengyu, Wang;Yuxin, Zhu;Jiqiang, Niu;Xueye, Chen;Yang, Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1666-1689
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    • 2021
  • The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.

CFD based simulations of flutter characteristics of ideal thin plates with and without central slot

  • Zhu, Zhi-Wen;Chen, Zheng-Qing;Gu, Ming
    • Wind and Structures
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    • v.12 no.1
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    • pp.1-19
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    • 2009
  • In this paper, the airflow around an ideal thin plate (hereafter referred to as ITP) with various ratios of central slot is simulated by using the finite-difference-method (FDM)-based Arbitrary-Lagrangian-Eulerian descriptions for the rigid oscillating body. The numerical procedure employs the second-order projection scheme to decouple the governing equations, and the multigrid algorithm with three levels to improve the computational efficiency in evaluating of the pressure equation. The present CFD method is validated through comparing the computed flutter derivatives of the ITP without slot to Theodorsen analytical solutions. Then, the unsteady aerodynamics of the ITP with and without central slot is investigated. It is found that even a smaller ratio of central slot of the ITP has notable effects on pressure distributions of the downstream section, and the pressure distributions on the downstream section will further be significantly affected by the slot ratio and the reduced wind speeds. Continuous increase of $A_2^*$ with the increase of central slot may be the key feature of the slotted ITP. Finally, flutter analyses based on the flutter derivatives of the slotted ITP are performed, and moreover, flutter instabilities of a scaled sectional model of a twin-deck bridge with various ratios of deck slot are investigated. The results confirm that the central slot is effective to improve bridge flutter stabilities, and that the flutter critical wind speeds increase with the increase of slot ratio.

Simulation Research on the Thermal Effects in Dipolar Illuminated Lithography

  • Yao, Changcheng;Gong, Yan
    • Journal of the Optical Society of Korea
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    • v.20 no.2
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    • pp.251-256
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    • 2016
  • The prediction of thermal effects in lithography projection objective plays a significant role in the real-time dynamic compensation of thermal aberrations. For the illuminated lithography projection objective, this paper applies finite element analysis to get the temperature distribution, surface deformation and stress data. To improve the efficiency, a temperature distribution function model is proposed to use for the simulation of thermal aberrations with the help of optical analysis software CODE V. SigFit is approved integrated optomechanical analysis software with the feature of calculating OPD effects due to temperature change, and it is utilized to prove the validation of the temperature distribution function. Results show that the impact of surface deformation and stress is negligible compared with the refractive index change; astigmatisms and 4-foil aberrations dominate in the thermal aberration, about 1.7 λ and 0.45 λ. The system takes about one hour to reach thermal equilibrium and the contrast of the imaging of dense lines get worse as time goes on.

A novel approach of ship wakes target classification based on the LBP-IBPANN algorithm

  • Bo, Liu;Yan, Lin;Liang, Zhang
    • Ocean Systems Engineering
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    • v.4 no.1
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    • pp.53-62
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    • 2014
  • The detection of ship wakes image can demonstrate substantial information regarding on a ship, such as its tonnage, type, direction, and speed of movement. Consequently, the wake target recognition is a favorable way for ship identification. This paper proposes a Local Binary Pattern (LBP) approach to extract image features (wakes) for training an Improved Back Propagation Artificial Neural Network (IBPANN) to identify ship speed. This method is applied to sort and recognize the ship wakes of five different speeds images, the result shows that the detection accuracy is satisfied as expected, the average correctness rates of wakes target recognition at the five speeds may be achieved over 80%. Specifically, the lower ship's speed, the better accurate rate, sometimes it's accuracy could be close to 100%. In addition, one significant feature of this method is that it can receive a higher recognition rate than the nearest neighbor classification method.

SVC: Secure VANET-Assisted Remote Healthcare Monitoring System in Disaster Area

  • Liu, Xuefeng;Quan, Hanyu;Zhang, Yuqing;Zhao, Qianqian;Liu, Ling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.3
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    • pp.1229-1248
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    • 2016
  • With the feature of convenience and low cost, remote healthcare monitoring (RHM) has been extensively used in modern disease management to improve the quality of life. Due to the privacy of health data, it is of great importance to implement RHM based on a secure and dependable network. However, the network connectivity of existing RHM systems is unreliable in disaster area because of the unforeseeable damage to the communication infrastructure. To design a secure RHM system in disaster area, this paper presents a Secure VANET-Assisted Remote Healthcare Monitoring System (SVC) by utilizing the unique "store-carry-forward" transmission mode of vehicular ad hoc network (VANET). To improve the network performance, the VANET in SVC is designed to be a two-level network consisting of two kinds of vehicles. Specially, an innovative two-level key management model by mixing certificate-based cryptography and ID-based cryptography is customized to manage the trust of vehicles. In addition, the strong privacy of the health information including context privacy is taken into account in our scheme by combining searchable public-key encryption and broadcast techniques. Finally, comprehensive security and performance analysis demonstrate the scheme is secure and efficient.

An experimental study on tailings deposition characteristics and variation of tailings dam saturation line

  • Wang, Guangjin;Tian, Sen;Hu, Bin;Kong, Xiangyun;Chen, Jie
    • Geomechanics and Engineering
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    • v.23 no.1
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    • pp.85-92
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    • 2020
  • This study adopted soil test and laboratory physical model experiments to simulate the tailings impoundment accumulation process according to the principle of similarity. Relying on the practical engineering, it analyzed the tailings deposition characteristics on dry beach surface during the damming process, as well as the variation rules of dam saturation line. Results suggested that, the tailings particles gradually became finer along the dry beach surface to inside the impoundment. The particle size suddenly changed at the junction between the deposited beach and the water surface, which displayed an obvious coarsening phenomenon. Besides, the deposited beach exhibited the vertical feature of coarse upward and fine downward on the whole. Additionally, in the physical model, the saturation line elevated with the increase in dam height, and its amplitude was relatively obvious within the range of 1.0-4.5 m away from the initial dam. Under flood condition, the saturation line height was higher than that under normal condition on the whole, with the maximum height difference of 4 cm. This study could provide an important theoretical basis for further studies on dam failure experiments and the evolution rules of leaked tailings flow.

Multi-mode cable vibration control using MR damper based on nonlinear modeling

  • Huang, H.W.;Liu, T.T.;Sun, L.M.
    • Smart Structures and Systems
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    • v.23 no.6
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    • pp.565-577
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    • 2019
  • One of the most effective countermeasures for mitigating cable vibration is to install mechanical dampers near the anchorage of the cable. Most of the dampers used in the field are so-called passive dampers where their parameters cannot be changed once designed. The parameters of passive dampers are usually determined based on the optimal damper force obtained from the universal design curve for linear dampers, which will provide a maximum additional damping for the cable. As the optimal damper force is chosen based on a predetermined principal vibration mode, passive dampers will be most effective if cable undergoes single-mode vibration where the vibration mode is the same as the principal mode used in the design. However, in the actual engineering practice, multi-mode vibrations are often observed for cables. Therefore, it is desirable to have dampers that can suppress different modes of cable vibrations simultaneously. In this paper, MR dampers are proposed for controlling multi-mode cable vibrations, because of its ability to change parameters and its adaptability of active control without inquiring large power resources. Although the highly nonlinear feature of the MR material leads to a relatively complex representation of its mathematical model, effective control strategies can still be derived for suppressing multi-mode cable vibrations based on nonlinear modelling, as proposed in this paper. Firstly, the nonlinear Bouc-wen model is employed to accurately portray the salient characteristics of the MR damper. Then, the desired optimal damper force is determined from the universal design curve of friction dampers. Finally, the input voltage (current) of MR damper corresponding to the desired optimal damper force is calculated from the nonlinear Bouc-wen model of the damper using a piecewise linear interpolation scheme. Numerical simulations are carried out to validate the effectiveness of the proposed control algorithm for mitigating multi-mode cable vibrations induced by different external excitations.

A Study on Improving License Plate Recognition Performance Using Super-Resolution Techniques

  • Kyeongseok JANG;Kwangchul SON
    • Korean Journal of Artificial Intelligence
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    • v.12 no.3
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    • pp.1-7
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    • 2024
  • In this paper, we propose an innovative super-resolution technique to address the issue of reduced accuracy in license plate recognition caused by low-resolution images. Conventional vehicle license plate recognition systems have relied on images obtained from fixed surveillance cameras for traffic detection to perform vehicle detection, tracking, and license plate recognition. However, during this process, image quality degradation occurred due to the physical distance between the camera and the vehicle, vehicle movement, and external environmental factors such as weather and lighting conditions. In particular, the acquisition of low-resolution images due to camera performance limitations has been a major cause of significantly reduced accuracy in license plate recognition. To solve this problem, we propose a Single Image Super-Resolution (SISR) model with a parallel structure that combines Multi-Scale and Attention Mechanism. This model is capable of effectively extracting features at various scales and focusing on important areas. Specifically, it generates feature maps of various sizes through a multi-branch structure and emphasizes the key features of license plates using an Attention Mechanism. Experimental results show that the proposed model demonstrates significantly improved recognition accuracy compared to existing vehicle license plate super-resolution methods using Bicubic Interpolation.

Adaptable Center Detection of a Laser Line with a Normalization Approach using Hessian-matrix Eigenvalues

  • Xu, Guan;Sun, Lina;Li, Xiaotao;Su, Jian;Hao, Zhaobing;Lu, Xue
    • Journal of the Optical Society of Korea
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    • v.18 no.4
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    • pp.317-329
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    • 2014
  • In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.