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Jiapeng Wu - IEEE Xplore Author Profile
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Jiapeng Wu

Publications
3
Citations
1
Publications by Year
20232025
Co-Authors:
Show All Co-Authors (7)
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Jiapeng Wu

Affiliation

School of Mechanical Engineering
Dongguan University of Technology
Dongguan, China
Department of Computer Science and Artificial Intelligence
Seville University
Sevilla, Spain

Publication Topics

Biography

Jiapeng Wu received the B.Sc. degree in industrial engineering from Nanchang Hangkong University, Nanchang, China, in 2017, and the M.Sc. degree in industrial engineering from the Guangdong University of Technology, Guangzhou, China, in 2020. Since 2022, he has been working toward the Ph.D. degree in computer science with the Seville University, Seville, Spain.,His research interests include prognostic and health management, artificial intelligence, and data-driven modeling.(Based on document published on 17 April 2024).
Publications
3
Citations
1
Publications by Year
20232025
Co-Authors:
Show All Co-Authors (7)
Author's Published Works

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Attention-Based Multisignal Representation of High-Resolution Time Series: A Fault Detection Method for Industrial Machinery

Diego Cabrera;Jiapeng Wu;Mariela Cerrada;René-Vinicio Sánchez;Fernando Sancho;Jianyu Long;Chuan Li

IEEE Transactions on Industrial Electronics
Year: 2025 | Early Access Article |
Data-driven fault detection in prognostic and health management research poses significant challenges, particularly with few measurements to model complex machinery health conditions. Approaches requiring data in one or many faulty conditions are impractical for actual use cases where only healthy condition data exist. Most of the existing methods for this scenario rely on feature-based representa...Show More

Attention-Based Multisignal Representation of High-Resolution Time Series: A Fault Detection Method for Industrial Machinery

Diego Cabrera;Jiapeng Wu;Mariela Cerrada;René-Vinicio Sánchez;Fernando Sancho;Jianyu Long;Chuan Li

Year: 2025 | Early Access Article |

Fault Diagnosis Generalization Improvement Through Contrastive Learning for a Multistage Centrifugal Pump

Jiapeng Wu;Diego Cabrera;Mariela Cerrada;René-Vinicio Sánchez;Fernando Sancho;Edgar Estupinan

IEEE Transactions on Reliability
Year: 2025 | Volume: 74, Issue: 1 | Journal Article |
Cited by: Papers (1)
Data scarcity in prognostic and health management research presents a significant challenge, often hindering the performance of supervised models due to the difficulty of acquiring diverse fault mode data during prolonged faultless operation. Conversely, nominal operating condition (NOC) data, including both healthy and varied faulty data, are more readily available due to predelivery inspection. ...Show More

Fault Diagnosis Generalization Improvement Through Contrastive Learning for a Multistage Centrifugal Pump

Jiapeng Wu;Diego Cabrera;Mariela Cerrada;René-Vinicio Sánchez;Fernando Sancho;Edgar Estupinan

Year: 2025 | Volume: 74, Issue: 1 | Journal Article |

A Simple Yet Effective Data Augmentation for Self-Supervised Multi-stage Centrifugal Pump (MCP) Anomaly Detection

Jiapeng Wu;Diego Cabrera;Mariela Cerrada;Fernando Sancho

2023 IEEE Seventh Ecuador Technical Chapters Meeting (ECTM)
Year: 2023 | Conference Paper |
Anomaly detection tasks benefit from self-supervised learning techniques, where models predict or reconstruct parts of augmented input data without relying on explicit human-provided labels. However, many existing self-supervised learning methods employ data augmentation techniques without sufficient justification for their effectiveness. In this study, we present a simple but novel data augmentat...Show More

A Simple Yet Effective Data Augmentation for Self-Supervised Multi-stage Centrifugal Pump (MCP) Anomaly Detection

Jiapeng Wu;Diego Cabrera;Mariela Cerrada;Fernando Sancho

Year: 2023 | Conference Paper |

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