On-line monitoring of the machining processes provides to detect the amount and type of
tool wear which is critical for the determination of remaining useful lifetime of cutting tool …

Abstract In the “Industry 4.0” era, autonomous and self-adaptive industrial machining attracts
significant attention in professional manufacturing. This trend originates from the rising …

This paper introduces a new intelligent integration between an IoT platform and deep
learning neural network (DNN) algorithm for the online monitoring of computer numerical …

Chatter is a self-excited vibration phenomenon occurring in the cutting process, and the
onset of chatter will result in the worse machined surface and the redistribution of frequency …

Feature selection represents the main challenge against the classification strategies for
several applications of signal processing. Besides, the high computational speed and …

Mandelbrot set and Julia set are two very important investigations in complex dynamics, and
represented the collection of all complex numbers C based on the function fcz= z 2+ c …

Fault diagnosis is important to the timely repair of the power transformer. However, machine
learning has not been exploited effectively for fault diagnosis due to the limitation of multi …

Manufacturing companies increasingly become “smarter” as a result of the Industry 4.0
revolution. Multiple sensors are used for industrial monitoring of machines and workers in …

Among the diverse challenges in machining processes, chatter has a significant detrimental
effect on surface quality and tool life, and it is a major limitation factor in achieving higher …

To improve the accuracy of bearing fault diagnosis in a multisensor monitoring environment,
it is necessary to obtain more accurate and effective fault classification features for bearings …