# Automated location of steel truss bridge damage using machine learning and raw strain sensor data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automated-location-of-steel-truss-bridge-damage-using-machine-learning-and-raw/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Fulvio Parisi,Agostino Marcello Mangini,Maria Pia Fanti,José M. Adam |
| Citations | 64 |
| DOI | 10.1016/j.autcon.2022.104249 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | green |
| OA URL | http://hdl.handle.net/10251/190868 |
| OpenAlex ID | https://openalex.org/W4225113214 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Agostino Marcello Mangini](https://scholariq.org/researchers/agostino-marcello-mangini/)

## Paper primary topic

- [Time Series Analysis and Forecasting](https://scholariq.org/topics/time-series-analysis-and-forecasting/)

## Paper topics

- [Time Series Analysis and Forecasting](https://scholariq.org/topics/time-series-analysis-and-forecasting/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Structural Health Monitoring Techniques](https://scholariq.org/topics/structural-health-monitoring-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.