Multi-Sensor Fusion Technology for Feature Extraction and Intelligent Fault Diagnosis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 24 June 2026 | Viewed by 8
Special Issue Editors
Interests: fault perception and intelligent diagnosis-prediction methods for fluid machinery; health management and intelligent operation-m maintenance strategies for mechatronic-hydraulic equipment
Interests: fluid machinery; intelligent control; signal processing; fault diagnosis; intelligent maintenance
Special Issues, Collections and Topics in MDPI journals
Interests: electro-hydraulic hybrid drive and intelligent control strategies for mechanical equipment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Multi-sensor fusion technology significantly enhances the accuracy and robustness of fault diagnosis by integrating heterogeneous sensor data to build a global perception model of environments or equipment. In fields such as industrial manufacturing and agricultural machinery, individual sensors are prone to interference from noise, occlusion, and other factors, while multi-source data fusion can compensate for information blind spots, enabling early fault warning and precise localization.
This Special Issue primarily includes, but is not limited to, research on signal processing methods and data fusion methods. Fusion technologies are mainly signal-level fusion, feature-level fusion, decision-level fusion, and hybrid fusion. Main applications include industrial equipment health management, intelligent monitoring of agricultural machinery, and perception systems for autonomous vehicles.
Dr. Shengnan Tang
Dr. Yong Zhu
Dr. Qiang Gao
Guest Editors
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Keywords
- feature extraction
- fault diagnosis
- multi-sensor fusion
- signal-level fusion
- feature-level fusion
- decision-level fusion
- hybrid fusion
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