Data Mining Practical Machine Learning Tools and Techniques

Artificial intelligence for fault diagnosis of rotating machinery: A review

Applications of machine learning to machine fault diagnosis: A review and roadmap

Wavelets for fault diagnosis of rotary machines: A review with applications

Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in the first convolutional layer for extracting features and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform the state-of-the-art DNN model which is based on frequency features under different working load and noisy environment conditions.

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

Objective and subjective responses of seated subjects while reading Hindi newspaper under multi axis whole-body vibration

Vibration Response Analysis of Doubly Clamped Single Walled Wavy Carbon Nanotube Based Nanomechanical Sensors

Modal analysis of functionally graded piezoelectric material plates

Vibration Analysis of Single Walled Boron Nitride Nanotube Based Nanoresonators

Nonlinear vibrational behavior of a single-walled carbon nanotube based mass sensors is considered The modeling involves stretching of the mid plane and damping The equation of motion involves two nonlinear terms due to the curved geometry and the stretching of the central plane due to the bridged boundary conditions The manifestation of instability and chaos in the dynamic response is observed The regions of periodic, sub-harmonic and chaotic behavior are clearly seen to be dependent on added mass and the surface deviations Poincare maps and frequency spectra are used to explicate and demonstrate the miscellany of the system behavior

Chaotic response analysis of single-walled carbon nanotube due to surface deviations

S. P. Harsha

Papers

Objective and subjective responses of seated subjects while reading Hindi newspaper under multi axis whole-body vibration

Vibration Response Analysis of Doubly Clamped Single Walled Wavy Carbon Nanotube Based Nanomechanical Sensors

Modal analysis of functionally graded piezoelectric material plates

Vibration Analysis of Single Walled Boron Nitride Nanotube Based Nanoresonators

Chaotic response analysis of single-walled carbon nanotube due to surface deviations