Publications

Authors:

Cordoni, Francesco; Bacchiega, Gianluca; Bondani, Giulio; Radu, Robert; Muradore, Riccardo

Title:

A multi–modal unsupervised fault detection system based on power signals and thermal imaging via deep AutoEncoder neural network

Year:

2022

Type of item:

Articolo in Rivista

Tipologia ANVUR:

Articolo su rivista

Language:

Inglese

Referee:

Sì

Name of journal:

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

ISSN of journal:

0952-1976

N° Volume:

110

Number or Folder:

104729

Page numbers:

1-9

Keyword:

Auto-encoder neural network, Deep convolutional neural network, Deep Learning, Fault detection and isolation, Neural networks, Predictive maintenance, Thermal camera, Unsupervised learning

Short description of contents:

In this paper a multi-modal unsupervised Deep Learning based algorithm for fault detection is proposed. Such method is applied to real data from a testing procedure implemented on an industrial production line. Both thermal images and current and power measurements coming from industrial refrigerators are collected. The considered dataset is highly unbalanced with the vast majority of samples being healthy. Thermal images are processed via a Deep Convolutional neural network. The features extracted from the thermal images are thus merged to structured data of power, current and temperature. Therefore, a Deep Auto-Encoder is trained on the dataset to signal anomalies corresponding to faults in the refrigerators. Three different methods are trained and compared: (1) an automatic method in which an expert extracts relevant features from thermal images without using the image recognition module; (2) a semi-automatic method where the convolutional neural network is applied to regions of interest within the thermal images selected by an expert operator; (3) a fully automatic method in which the Deep convolutional network processes the whole thermal image without any human intervention. The three methods show comparable results with nevertheless slight differences.

Product ID:

125505

Handle IRIS:

11562/1060622

Last Modified:

January 23, 2025

Bibliographic citation:

Cordoni, Francesco; Bacchiega, Gianluca; Bondani, Giulio; Radu, Robert; Muradore, Riccardo, A multi–modal unsupervised fault detection system based on power signals and thermal imaging via deep AutoEncoder neural network «ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE» , vol. 110 , n. 104729 , 2022 , pp. 1-9

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