In this paper, we propose a two-stage algorithm for real-time fault detection and identification
of industrial plants. Our proposal is based on the analysis of selected features using …

This paper presents an approach to fault diagnosis with online detection of novel faults and
automatic learning using fuzzy clustering techniques. In the off-line learning stage, the …

Fault detection in industrial processes is a field of application that has gaining considerable
attention in the past few years, resulting in a large variety of techniques and methodologies …

This work proposes a methodology for fault identification of dynamic systems using an
online evolving approach. The proposed methodology is divided into three stages: pre …

The current research paper proposes a novel information processing Deep Learning
framework for unsupervised fault detection applications, where during the training process …

Modeling and recognizing faults and outages in a real-world power grid is a challenging
task, in line with the modern concept of Smart Grids. The availability of Smart Sensors and …

Industrial fault diagnosis has been investigated for many years, and many approaches have
been proposed to identify industrial faults. However, the size of the actual training set is …

Preventive maintenance plays an important role in Heating, Ventilation and Air Conditioning
(HVAC) system. One cost effective strategy is the development of analytic fault detection and …

In this article, a methodology based on machine learning for fault detection in continuous
processes is presented. It aims to monitor fully distributed scenarios, such as the Tennessee …

Today, failure modes characterization and early detection is a key issue in complex assets.
This is due to the negative impact of corrective operations and the conservative strategies …