Ernst Niederleithinger

Federal Institute For Materials Research and Testing

Papers

2

Total Citations

33

H-Index

2

About

Ernst Niederleithinger is a leading figure in non-destructive testing for civil engineering (NDT-CE), with a focus on advancing sensor fusion and automated inspection of concrete infrastructure. His research centers on developing intelligent methods to detect near-surface defects—such as corrosion-induced damage in reinforced concrete—by integrating data from multiple sensors, including potential mapping, concrete cover assessment, and moisture detection. A key contribution is his work on unsupervised clustering algorithms for image fusion, which significantly improves defect detection reliability compared to single-sensor approaches. His 2014 paper on this topic has garnered 30 citations, reflecting its influence in the field. Additionally, he has pioneered the use of multi-sensor robotic systems, notably the BetoScan platform at BAM (Federal Institute for Materials Research and Testing), which enables contactless, simultaneous data collection from parking garage floors. This work addresses critical real-world challenges in infrastructure maintenance. Niederleithinger’s achievements underscore his role in bridging advanced computational techniques with practical NDT applications, making him a key reference for researchers and engineers working on automated, high-fidelity inspection of aging concrete structures.

Research Focus

Key Achievements

2
H-Index
2
Papers
33
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Image Fusion for Improved Detection of Near-Surface Defects in NDT-CE Using Unsupervised Clustering Methods
30 citations · 2014
📈 Most Prolific Year: 2014 (2 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Federal Institute For Materials Research and Testing

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago