Browsing by Author "Richter, Bertram"

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    Open Access
    Artificial data set for benchmarking pre-processing algorithms for distributed fiber optic strain data
    (Technische Universität Dresden, 2024-11-28) Richter, Bertram
    Distributed strains sensing (DSS) with distributed fiber optic sensors (DFOS) has great potential for structural health monitoring (SHM). Raw DSS data might contain different types of disturbances caused by the measurement principle of DFOS. The disturbance types are (i) misreadings called strain reading anomolies (SRA), (ii) missing values called dropouts, and (iii) noise. Hence, pre-processing (the process of removing or reducing the disturbances) is key for a reliable evaluation of DSS data. Many different pre-processing approaches/algorithms exist. The assessment, how well an algorithms performs in removing the disturbances is done by benchmarking. This judgement requires a known "ground truth" (disturbance free signal). As all measurements show noise, this benchmarking needs to be carried out on an artifical data set. The aim of this benchmark data set is to simulate realistic DSS data. The characteristics of the benchmark data set is described in in detail in the accompanying paper available at [10.3390/s24237454](https://doi.org/10.3390/s24237454). To simulate different use cases, the data set contains five scenarios. SRAs, dropouts and noise are simulated using simple random processes. The values for SRAs are extracted from the data set available at [10.25532/OPARA-671](https://doi.org/10.25532/OPARA-671). This dataset is available at [10.25532/OPARA-644](https://doi.org/10.25532/OPARA-644) and accompanies the paper [10.3390/s24237454](https://doi.org/10.3390/s24237454).
  • Item
    Open Access
    Monitoring Data of the openLAB Research Bridge (2024-02-01 to 2024-10-31) and building information
    (Technische Universität Dresden, 2025-01-15) Jansen, Andreas; Richter, Bertram; Röder, Robert; Herbers, Max; Marx, Steffen
    This dataset presents Structural Health Monitoring (SHM) data from the openLAB research bridge, a large-scale laboratory structure located in Bautzen, Germany. Following an initial one-year reference phase, the bridge will undergo a series of load tests designed to induce significant structural damage. This open-access dataset provides researchers with a rare opportunity to validate SHM methodologies under near-real-world conditions. The current publication includes data from the undamaged bridge, covering the period from 2024-02-01 to 2024-10-31. Additional repositories will be published periodically as new data become available. The bridge is equipped with a comprehensive monitoring system featuring fiber optic and electrical sensors that capture both structural behavior and environmental conditions (e.g., air temperature, humidity, and solar radiation). In this initial release, data is sourced from an electrical Gantner Instruments measurement system (Q.station 101T, with various Q.bloxx modules). The dataset includes measurements of acceleration, tilt, air temperature, humidity, and solar radiation. Data is recorded continuously at 10-minute intervals, with additional triggered measurements during non-damaging load tests conducted with a test vehicle or in response to increased vibration activity. The repository provides the data in Comma Separated Values (CSV) format. Each file includes a header specifying the names of the data columns. Additional details, such as units and sampling frequency, are provided in this README file. Each CSV file contains a Timestamp column that records the time of each sample as a datetime string in ISO 8601 format, without time zone information. All timestamps are in Coordinated Universal Time (UTC). Sensor data is represented as decimal numbers. The data is accompanied with structural plans of the bridge and the installed monitoring system. This dataset is available at [10.25532/OPARA-660](https://doi.org/10.25532/OPARA-660).