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  • Open Access

    ARTICLE

    Numerical Analysis of Flow-Induced Vibration and Noise Generation in a Variable Cross-Section Channel

    Youhao Wang1, Chuntian Zhe1, Chang Guo2, Jinpeng Li3, Jinheng Li3, Shen Cheng2, Zitian Wu1, Suoying He1, Ming Gao1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.12, pp. 2965-2980, 2023, DOI:10.32604/fdmp.2023.029292

    Abstract Flow channels with a variable cross-section are important components of piping system and are widely used in various fields of engineering. Using a finite element method and modal analysis theory, flow-induced noise, mode shapes, and structure-borne noise in such systems are investigated in this study. The results demonstrate that the maximum displacement and equivalent stress are located in the part with variable cross-sectional area. The average excitation force on the flow channel wall increases with the flow velocity. The maximum excitation force occurs in the range of 0–20 Hz, and then it decreases gradually in the range of 20–1000 Hz.… More >

  • Open Access

    ARTICLE

    PAN-DeSpeck: A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

    Saima Yasmeen1, Muhammad Usman Yaseen1,*, Syed Sohaib Ali2, Moustafa M. Nasralla3, Sohaib Bin Altaf Khattak3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3671-3689, 2023, DOI:10.32604/cmc.2023.041195

    Abstract SAR images commonly suffer from speckle noise, posing a significant challenge in their analysis and interpretation. Existing convolutional neural network (CNN) based despeckling methods have shown great performance in removing speckle noise. However, these CNN-based methods have a few limitations. They do not decouple complex background information in a multi-resolution manner. Moreover, they have deep network structures that may result in many parameters, limiting their applicability to mobile devices. Furthermore, extracting key speckle information in the presence of complex background is also a major problem with SAR. The proposed study addresses these limitations by introducing a lightweight pyramid and attention-based… More >

  • Open Access

    ARTICLE

    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

    Guangfei Jia*, Fengwei Guo, Zhe Wu, Suxiao Cui, Jiajun Yang

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 383-405, 2023, DOI:10.32604/sdhm.2023.026885

    Abstract With the development of multi-signal monitoring technology, the research on multiple signal analysis and processing has become a hot subject. Mechanical equipment often works under variable working conditions, and the acquired vibration signals are often non-stationary and nonlinear, which are difficult to be processed by traditional analysis methods. In order to solve the noise reduction problem of multiple signals under variable speed, a COT-DCS method combining the Computed Order Tracking (COT) based on Chirplet Path Pursuit (CPP) and Distributed Compressed Sensing (DCS) is proposed. Firstly, the instantaneous frequency (IF) is extracted by CPP, and the speed is obtained by fitting.… More > Graphic Abstract

    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

  • Open Access

    PROCEEDINGS

    Mechanism of the Passive Tap-Scan Damage Detection Method

    Zhuyou Hu1, Ping Lin2,3, He Guo2,3, Yumei Zhang2,3, Zhihai Xiang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

    Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

  • Open Access

    ARTICLE

    Research on Narrowband Line Spectrum Noise Control Method Based on Nearest Neighbor Filter and BP Neural Network Feedback Mechanism

    Shuiping Zhang1,2, Xi Liang3, Lin Shi2, Lei Yan4, Jun Tang1,2,*

    Sound & Vibration, Vol.57, pp. 29-44, 2023, DOI:10.32604/sv.2023.041350

    Abstract The filter-x least mean square (FxLMS) algorithm is widely used in active noise control (ANC) systems. However, because the algorithm is a feedback control algorithm based on the minimization of the error signal variance to update the filter coefficients, it has a certain delay, usually has a slow convergence speed, and the system response time is long and easily affected by the learning rate leading to the lack of system stability, which often fails to achieve the desired control effect in practice. In this paper, we propose an active control algorithm with nearest-neighbor trap structure and neural network feedback mechanism… More > Graphic Abstract

    Research on Narrowband Line Spectrum Noise Control Method Based on Nearest Neighbor Filter and BP Neural Network Feedback Mechanism

  • Open Access

    ARTICLE

    Context Awareness by Noise-Pattern Analysis of a Smart Factory

    So-Yeon Lee1, Jihoon Park1, Dae-Young Kim2,*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1497-1514, 2023, DOI:10.32604/cmc.2023.034914

    Abstract Recently, to build a smart factory, research has been conducted to perform fault diagnosis and defect detection based on vibration and noise signals generated when a mechanical system is driven using deep-learning technology, a field of artificial intelligence. Most of the related studies apply various audio-feature extraction techniques to one-dimensional raw data to extract sound-specific features and then classify the sound by using the derived spectral image as a training dataset. However, compared to numerical raw data, learning based on image data has the disadvantage that creating a training dataset is very time-consuming. Therefore, we devised a two-step data preprocessing… More >

  • Open Access

    PROCEEDINGS

    Mechanism of the Passive Tap-Scan Damage Detection Method

    Zhuyou Hu1, Ping Lin2,3, He Guo2,3, Yumei Zhang2,3, Zhihai Xiang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

    Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

  • Open Access

    ARTICLE

    Multiple Data Augmentation Strategy for Enhancing the Performance of YOLOv7 Object Detection Algorithm

    Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal on Artificial Intelligence, Vol.5, pp. 15-30, 2023, DOI:10.32604/jai.2023.041341

    Abstract The object detection technique depends on various methods for duplicating the dataset without adding more images. Data augmentation is a popular method that assists deep neural networks in achieving better generalization performance and can be seen as a type of implicit regularization. This method is recommended in the case where the amount of high-quality data is limited, and gaining new examples is costly and time-consuming. In this paper, we trained YOLOv7 with a dataset that is part of the Open Images dataset that has 8,600 images with four classes (Car, Bus, Motorcycle, and Person). We used five different data augmentations… More >

  • Open Access

    ARTICLE

    An Improved Soft Subspace Clustering Algorithm for Brain MR Image Segmentation

    Lei Ling1, Lijun Huang2, Jie Wang2, Li Zhang2, Yue Wu2, Yizhang Jiang1, Kaijian Xia2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2353-2379, 2023, DOI:10.32604/cmes.2023.028828

    Abstract In recent years, the soft subspace clustering algorithm has shown good results for high-dimensional data, which can assign different weights to each cluster class and use weights to measure the contribution of each dimension in various features. The enhanced soft subspace clustering algorithm combines interclass separation and intraclass tightness information, which has strong results for image segmentation, but the clustering algorithm is vulnerable to noisy data and dependence on the initialized clustering center. However, the clustering algorithm is susceptible to the influence of noisy data and reliance on initialized clustering centers and falls into a local optimum; the clustering effect… More >

  • Open Access

    TUTORIAL

    Loss Factors and their Effect on Resonance Peaks in Mechanical Systems

    Roman Vinokur*

    Sound & Vibration, Vol.57, pp. 1-13, 2023, DOI:10.32604/sv.2023.041784

    Abstract The loss factors and their effects on the magnitude and frequency of resonance peaks in various mechanical systems are reviewed for acoustic, vibration, and vibration fatigue applications. The main trends and relationships were obtained for linear mechanical models with hysteresis damping. The well-known features (complex module of elasticity, total loss factor, etc.) are clarified for practical engineers and students, and new results are presented (in particular, for 2-DOF in-series models with hysteresis friction). The results are of both educational and practical interest and may be applied for NVH analysis and testing, mechanical and aeromechanical design, and noise and vibration control… More >

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