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  • Open Access

    ARTICLE

    Use of Discrete Wavelet Features and Support Vector Machine for Fault Diagnosis of Face Milling Tool

    C. K. Madhusudana1, N. Gangadhar1, Hemantha Kumar, Kumar,*,1, S. Narendranath1

    Structural Durability & Health Monitoring, Vol.12, No.2, pp. 111-127, 2018, DOI: 10.3970/sdhm.2018.01262

    Abstract This paper presents the fault diagnosis of face milling tool based on machine learning approach. While machining, spindle vibration signals in feed direction under healthy and faulty conditions of the milling tool are acquired. A set of discrete wavelet features is extracted from the vibration signals using discrete wavelet transform (DWT) technique. The decision tree technique is used to select significant features out of all extracted wavelet features. C-support vector classification (C-SVC) and ν-support vector classification (ν-SVC) models with different kernel functions of support vector machine (SVM) are used to study and classify the tool condition based on selected features.… More >

  • Open Access

    ARTICLE

    Wavelet-based Inclusion Detection in Cantilever Beams

    Zheng Li1,2, Wei Zhang1, Kezhuang Gong1

    CMC-Computers, Materials & Continua, Vol.9, No.3, pp. 209-228, 2009, DOI:10.3970/cmc.2009.009.209

    Abstract In this paper, continuous wavelet transform has been applied to inclusion detection in cantilever beams. By means of FEM, a cantilever beam with an inclusion is subjected to an impact on its free end, and its stress wave propagation process is calculated. Here, two kinds of inclusions which are distinct in material behavior have been discussed. And we change the inclusion's sizes in the beam and set it in three different positions to simulate some complicated situations. For soft inclusion, the results show that the arrival times of incident and reflective wave are distinguishable by performing Gabor wavelet transform and… More >

  • Open Access

    ARTICLE

    A Robust Image Watermarking Scheme Using Z-Transform, Discrete Wavelet Transform and Bidiagonal Singular Value Decomposition

    N. Jayashree1,*, R. S. Bhuvaneswaran1

    CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 263-285, 2019, DOI:10.32604/cmc.2019.03924

    Abstract Watermarking is a widely used solution to the problems of authentication and copyright protection of digital media especially for images, videos, and audio data. Chaos is one of the emerging techniques adopted in image watermarking schemes due to its intrinsic cryptographic properties. This paper proposes a new chaotic hybrid watermarking method combining Discrete Wavelet Transform (DWT), Z-transform (ZT) and Bidiagonal Singular Value Decomposition (BSVD). The original image is decomposed into 3-level DWT, and then, ZT is applied on the HH3 and HL3 sub-bands. The watermark image is encrypted using Arnold Cat Map. BSVD for the watermark and transformed original image… More >

  • Open Access

    ARTICLE

    Robust Image Hashing via Random Gabor Filtering and DWT

    Zhenjun Tang1,*, Man Ling1, Heng Yao1, Zhenxing Qian2, Xianquan Zhang1, Jilian Zhang3, Shijie Xu1

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 331-344, 2018, DOI:10.3970/cmc.2018.02222

    Abstract Image hashing is a useful multimedia technology for many applications, such as image authentication, image retrieval, image copy detection and image forensics. In this paper, we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform (DWT). Specifically, robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map, and then are compressed via a single-level 2-D DWT. Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band. Many experiments with open image datasets are carried out and the results illustrate… More >

  • Open Access

    ARTICLE

    A Machine Learning Approach for MRI Brain Tumor Classification

    Ravikumar Gurusamy1, Dr Vijayan Subramaniam2

    CMC-Computers, Materials & Continua, Vol.53, No.2, pp. 91-108, 2017, DOI:10.3970/cmc.2017.053.091

    Abstract A new method for the denoising, extraction and tumor detection on MRI images is presented in this paper. MRI images help physicians study and diagnose diseases or tumors present in the brain. This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis. The ambiguity of Magnetic Resonance (MR) image features is solved in a simpler manner. The MRI image acquired from the machine is subjected to analysis in the work. The real-time data is used for the analysis. Basic preprocessing is performed using various filters for noise removal. The de-noised image is… More >

  • Open Access

    ARTICLE

    Identification of Damaged Teeth in Gears using Wavelet Transform Applied to the Angular Vibration Signal

    P.A. Meroño1, F.C. Gómez2, F. Marín1

    CMC-Computers, Materials & Continua, Vol.47, No.2, pp. 107-125, 2015, DOI:10.3970/cmc.2015.047.107

    Abstract This work represents a comparative study of Wavelet Transform of angular vibration signal and the traditional Fourier analysis applied to the signals of angular vibration, in one transmission which involve gears. How it is known, the elastic deformation of the material, together with the superficial irregularities of the teeth due to wear, provoke characteristic angular oscillations, which make it possible to distinguish between the regular functioning of a mechanism in good condition and the angular vibrations provoked by wear and the superficial irregularities of teeth in poor condition. However, the character of the vibrations produced in such circumstances means that… More >

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