[HTML][HTML] A review on autoencoder based representation learning for fault detection and diagnosis in industrial processes

J Qian, Z Song, Y Yao, Z Zhu, X Zhang - Chemometrics and Intelligent …, 2022 - Elsevier
Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

A survey of mechanical fault diagnosis based on audio signal analysis

L Tang, H Tian, H Huang, S Shi, Q Ji - Measurement, 2023 - Elsevier
Mechanical fault diagnosis is one of the important technologies in the fourth industrial
revolution. In recent years, mechanical fault diagnosis based on audio signal analysis …

Anomalous sound event detection: A survey of machine learning based methods and applications

Z Mnasri, S Rovetta, F Masulli - Multimedia Tools and Applications, 2022 - Springer
With the development of multi-modal man-machine interaction, audio signal analysis is
gaining importance in a field traditionally dominated by video. In particular, anomalous …

TinyVers: A tiny versatile system-on-chip with state-retentive eMRAM for ML inference at the extreme edge

V Jain, S Giraldo, J De Roose, L Mei… - IEEE Journal of Solid …, 2023 - ieeexplore.ieee.org
Extreme edge devices or Internet-of-Things (IoT) nodes require both ultra-low power (ULP)
always-on (AON) processing as well as the ability to do on-demand sampling and …

Real time detection of acoustic anomalies in industrial processes using sequential autoencoders

B Bayram, TB Duman, G Ince - Expert Systems, 2021 - Wiley Online Library
Abstract Development of intelligent systems with the pursuit of detecting abnormal events in
real world and in real time is challenging due to difficult environmental conditions, hardware …

Deep unsupervised multi-modal fusion network for detecting driver distraction

Y Zhang, Y Chen, C Gao - Neurocomputing, 2021 - Elsevier
The risk of incurring a road traffic crash has increased year by year. Studies show that lack of
attention during driving is one of the major causes of traffic accidents. In this work, in order to …

Acoustic anomaly detection for machine sounds based on image transfer learning

R Müller, F Ritz, S Illium, C Linnhoff-Popien - arxiv preprint arxiv …, 2020 - arxiv.org
In industrial applications, the early detection of malfunctioning factory machinery is crucial. In
this paper, we consider acoustic malfunction detection via transfer learning. Contrary to the …

A large-scale benchmark dataset for anomaly detection and rare event classification for audio forensics

A Abbasi, ARR Javed, A Yasin, Z Jalil… - IEEE …, 2022 - ieeexplore.ieee.org
With the emergence of new digital technologies, a significant surge has been seen in the
volume of multimedia data generated from various smart devices. Several challenges for …

Anomalous sound detection with machine learning: A systematic review

EC Nunes - arxiv preprint arxiv:2102.07820, 2021 - arxiv.org
Anomalous sound detection (ASD) is the task of identifying whether the sound emitted from
an object is normal or anomalous. In some cases, early detection of this anomaly can …

[HTML][HTML] Reconstruction-based visual anomaly detection in wound rotor synchronous machine production using convolutional autoencoders and structural similarity

M Kohler, D Mitsios, C Endisch - Journal of Manufacturing Systems, 2025 - Elsevier
Manufacturing wound rotor synchronous machines (WRSMs) for electric vehicle traction
systems necessitates rigorous quality inspection to ensure optimal product performance and …