Fraunhofer Institute for Wind Energy Systems
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No full textThis dataset consists of 360 minutes of synchronized video and motion data gathered using
a wearable sensor vest equipped with 4 IMUs (one on each upper arm, two on the chest). The
data represents about 282 repetitions of a cyclical industrial assembly task performed by
5 different participants. The data has been annotated using six mid-level actions and a
null class. The class representation is highly imbalanced, as is the total amount of
cycles each participant has recorded.The dataset consists of tabular data saved in multiple CSV files. There are 26 columns in total: the timestamp in milliseconds, 24 columns of accelerometer and gyroscope data—4 of each sensor type with 3 axes per sensor, and an integer label column
Threshold of Toxicological Concern—An Update for Non-Genotoxic Carcinogens
No full textSupplementary MaterialThe project has been funded by the CEFIC LRI initiative.
This study received funding from the CEFIC LRI B18_2 Project and data from the updated CPDB databases provided by the CEFIC LRI B18 project. The funder was not involved in the study design, collection, analysis, interpretation of data, the decision to submit it for publication.A list of non-genotoxic carcinogens, with reference doses like no observed effect levels (NOELs) or bench mark doses
Realisierung der Sensormodule für die mobile Datenerfassung
No full textFür die Entwicklung des “Betriebssystems” der Sensormodule wurde das quelloffene Arduino-Framework eingesetzt, das speziell für die einfache und agile Programmierung von Microcontrollern auf Basis der Programmiersprache C++ entwickelt wurde. Das Framework verfügt aufgrund seiner sehr großen Nutzerbasis vor allem über eine Vielzahl externer Bibliotheken, die zur Ansteuerung verschiedenster Peripheriekomponenten wie beispielweise LoRaWAN-Funkmodulen durch einen Microcontroller benötigt werden.Ministerium für Umwelt, Klima und Energiewirtschaft Baden-WürttembergEnthalten sind 3D-Druckvorlagen für die Sensormodule, Schaltungsentwurf für das LoRaWAN Funkmodul, die Software für die Steuerung der Sensordatenerfassung, sowie verschiedene Bilder zur Illustration der Geräte und Montage
Experimentelle Charakterisierung piezoelektrischer Mikromembranpumpen für Medikamentendosierung
No full textSubcutaneous injection of medication is crucial for the treatment of many diseases. Especially if regular or continuous injections are beneficial, automated dosing units are advantageous. How-ever, existing devices are still large and therefore uncomfortable, visible under clothing, or inter-fere with physical activity. Thus, the development of small, energy efficient and reliable patch pumps or implantable systems is necessary and research on microelectromechanical system (MEMS) based drug delivery devices gained increasing interest. However, the requirements of medical application are not yet fully met and especially dosing precision and reliability pose a challenge for MEMS pumps. To enable further miniaturization, we propose a precise 5x5 mm² sil-icon micropump. Detailed experimental evaluation of ten pumps proves a backpressure capability with air of 12.5 ± 0.8 kPa, which indicates the ability to transport bubbles at moderate backpres-sures. The maximal water flow rate is 74 ± 6 µl/min and the pumps’ average blocking pressure is 51 kPa. The evaluation of the dosing precision for bolus deliveries with water and insulin shows a high repeatability of dosed package volumes. The pumps show a mean standard deviation of only 0.02 mg for 0.5 mg packages and therefore stay below the generally accepted 5% deviation, even for this extremely small amount. This high precision enables the combination with higher concen-trated medication and is the foundation for the development of an extremely miniaturized patch pump
Data Management Plan – Level 2
Get PDFAblative Fast Pyrolysis (AFP) is the first step in the BioMates-concept to convert herbaceous biomass into co-feed with reliable properties for conventional refineries (www.biomates.eu). The document provides the coding behind the identifiers used for samples and sample blends produced by Fraunhofer UMSICHT via AFP within the H2020-project BioMates.Adobe Acrobat Reade
Supplementary data
No full textMeasurement results of particle size analysis of investigated cobalt oxide catalyst. Differential thermal analysis investigation results of thermal response of catalyst towards methane and respective mass spectroscopy investigation.This work was supported by Fraunhofer Gesellschaft within the research project “FluMEMs” as well as the “Sustainability Center Freiburg” within the project “LeakAlert”.The commercially available STA-QMS (NETZSCH, STA 409 CD-QMS 403/5 SKIMMER) equipped with DTA sample carrier was used for investigation
Measurements of Vibrations and Acoustic Emissions on a Rotating Shaft
No full textEarly damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. The data analysis can be improved by applying machine learning algorithms and fusion of data from heterogeneous sensors. The paper (see ) presents an approach for a step-wise integration of classifications gained from vibration and acoustic emission sensors, in order to combine the information from signals acquired in the low and high frequency range. A test rig comprising a drive train and bearings with small artificial damages is used for acquisition of experimental data. The results indicate that an improvement of damage classification can be obtained using the proposed algorithm of combining classifiers for vibrations and acoustic emission. This dataset contains vibration data as well as acoustic emission data recorded on a rotating drive train. For vibration measurements, the setup is instrumented with ICP accelerometers (PCB 607A11, 100 mV/g) at the bearing holder frame of the motor and the bearing holder frame of the shaft. Both vibrational sensors are digitized by a DT 9837A USB-DAQ from (Measurement Computing GmbH). This 4-channel signal analyzer is equipped with a 24-bit ADC, that supports sample rates of up to 100 kSPS and is well suited for the vibration measurements. Acoustic emission signals (AE) are acquired by a piezo transducer (Vallen VS30V, 20 kHz – 80 kHz) connected to an AEP5 pre-amplifier for signal conditioning. These signals are digitized with an USB oscilloscope (PicoScope 2204A). This entry-level 2-channel oscilloscope features an 8-bit ADC with sample rates of up to 100 MSPS with an analog bandwidth of 10 MHz.This dataset was published in connection with some Jupyter notebooks. The notebooks are freely available via Github (https://github.com/deepinsights-analytica/mdpi-arci2021-paper) and contain examples for reading, analyzing, classifying and visualizing the data. The dataset contains the measured raw data (data//.csv) as well as metadata that describes the vibration and acoustic emission sensors (sensors/.json) and the configuration of all measurements (measurements/.json). A total of 29 measurements are included. For each measurement the the file vb.csv contains the vibration data: a timestamp in the first column followed by 8192 sensor values. It is sampled with a sampling rate of 8192 Hz. One line thus corresponds to a measurement time of one second. The ae.csv files with the acoustic emission data also contain a timestamp in the first column followed by 8000 sensor values. It is sampled at a sampling rate of 390625Hz. One line therefore corresponds to a measurement time of 20.48 ms. A file w.csv with the speeds was also recorded for each measurement. These files contain the time frames (begin and end timestamp) for the five rotational speeds: 600rpm, 1000rpm, 1400rpm, 1800rpm, 2200rpm). While the measurement for the vibration and the acoustic emission was carried out continuously for the different speeds, the phases with an almost constant speed can be extracted with the help of the time ranges based on the w.csv files
Simulation data set for deep drawing cups of DC04 steel sheets
No full textThis data set contains the results of 9999 finite element simulations of cup drawing processes that are conducted using the commercial software Abaqus/Explicit. For each process simulation, the input parameters (material dependent parameters and process parameters) were varied randomly. The material parameters were chosen based on typical fluctuations in DC04 steel sheets and possible process parameter settings following literature and norms
Experimentelle Charakterisierung, FEM Simulation und analytische Modellierung einer piezoelektrischen Mikroventils mit mehreren Ventilsitzgräben
No full textThis dataset contains experimental data as a characterisation of piezoelectric microvalves. Measurement data includes the actuator stroke measured using white light profilometry, as well as fluidic measurements of generated flow, passive flow, and leakage measured using coriflow flowmeters. Experimental data before and after 10^6 actuation cycles fatigue test is supplied. An COMSOL Multiphysics project file is given as part of an evaluation of a design parameter study as well as simulation results in form of csv data. Analytical modelling of leakage rates is implemented in python scripts and associated text files contain calculation results.This research was funded by the Bavarian Ministry of Economic Affairs, Regional Development and Energy, within the Bavarian funding program for research and development “Electronic Systems” under the grant number ESB071/002.The dataset contains .dat files for fluidic measurements; .txt files for stroke measurements; a .mph COMSOL Multiphysics project file with associated .csv result files, and .py Python scripts for analytical modelling. Experimental data, simulation files, and modelling files are collected in separate zip folders, respectively