[{"department":[{"_id":"DEP5023"}],"date_created":"2026-06-08T13:40:53Z","date_updated":"2026-06-09T06:42:59Z","user_id":"83781","doi":"10.5281/ZENODO.56358","title":"Typical Sensor Defects Dataset","year":"2016","citation":{"apa":"Ehlenbröker, J.-F., Mönks, U., &#38; Lohweg, V. (2016). <i>Typical Sensor Defects Dataset</i>. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.56358\">https://doi.org/10.5281/ZENODO.56358</a>","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ehlenbröker, Jan-Friedrich</span> ; <span style=\"font-variant:small-caps;\">Mönks, Uwe</span> ; <span style=\"font-variant:small-caps;\">Lohweg, Volker</span>: <i>Typical Sensor Defects Dataset</i> : Zenodo, 2016","chicago":"Ehlenbröker, Jan-Friedrich, Uwe Mönks, and Volker Lohweg. <i>Typical Sensor Defects Dataset</i>. Zenodo, 2016. <a href=\"https://doi.org/10.5281/ZENODO.56358\">https://doi.org/10.5281/ZENODO.56358</a>.","mla":"Ehlenbröker, Jan-Friedrich, et al. <i>Typical Sensor Defects Dataset</i>. Zenodo, 2016, <a href=\"https://doi.org/10.5281/ZENODO.56358\">https://doi.org/10.5281/ZENODO.56358</a>.","ieee":"J.-F. Ehlenbröker, U. Mönks, and V. Lohweg, <i>Typical Sensor Defects Dataset</i>. Zenodo, 2016. doi: <a href=\"https://doi.org/10.5281/ZENODO.56358\">10.5281/ZENODO.56358</a>.","van":"Ehlenbröker JF, Mönks U, Lohweg V. Typical Sensor Defects Dataset. Zenodo; 2016.","chicago-de":"Ehlenbröker, Jan-Friedrich, Uwe Mönks und Volker Lohweg. 2016. <i>Typical Sensor Defects Dataset</i>. Zenodo. doi:<a href=\"https://doi.org/10.5281/ZENODO.56358\">10.5281/ZENODO.56358</a>, .","ufg":"<b>Ehlenbröker, Jan-Friedrich/Mönks, Uwe/Lohweg, Volker</b>: Typical Sensor Defects Dataset, o. O. 2016.","bjps":"<b>Ehlenbröker J-F, Mönks U and Lohweg V</b> (2016) <i>Typical Sensor Defects Dataset</i>. Zenodo.","havard":"J.-F. Ehlenbröker, U. Mönks, V. Lohweg, Typical Sensor Defects Dataset, Zenodo, 2016.","short":"J.-F. Ehlenbröker, U. Mönks, V. Lohweg, Typical Sensor Defects Dataset, Zenodo, 2016.","ama":"Ehlenbröker JF, Mönks U, Lohweg V. <i>Typical Sensor Defects Dataset</i>. Zenodo; 2016. doi:<a href=\"https://doi.org/10.5281/ZENODO.56358\">10.5281/ZENODO.56358</a>"},"type":"research_data","publisher":"Zenodo","author":[{"last_name":"Ehlenbröker","full_name":"Ehlenbröker, Jan-Friedrich","first_name":"Jan-Friedrich","id":"1852"},{"full_name":"Mönks, Uwe","first_name":"Uwe","last_name":"Mönks","id":"88034"},{"first_name":"Volker","full_name":"Lohweg, Volker","orcid":"0000-0002-3325-7887","last_name":"Lohweg","id":"1804"}],"abstract":[{"lang":"eng","text":"\r\n\r\nThirteen datasets of sensor values, with one dataset without sensor defects (data_standard.csv). All other datasets are based on the dataset without a defect, with the values of Temp_Sensor_2 modified to simulate different sensor defects:\r\n\r\n    Sensor Drift: 1‰/hour (data_drift_0_001.csv), 2.5‰/hour (data_drift_0_0025.csv), 5‰/hour (data_drift_0_005.csv)\r\n    Sensor Offset: 1°C Offset (data_offset_1.csv), 2°Offset (data_offset_2.csv), 5°Offset (data_offset_5.csv)\r\n    Sensor Peaks: 1 Peak/Minute (data_peak_1.csv), 2 Peaks/Minute (data_peak_2.csv), 5 Peaks/Minute (data_peak_5.csv), 10 Peaks/Minute(data_peak_10.csv)\r\n    Sensor Noise: 10 dB SNR (data_noise_10dB.csv), 0 dB SNR (data_noise_0dB.csv)\r\n\r\nThe datasets are given as comma-separated values in text files. The first column in each file holds time stamps, while the following columns hold the sensor values. The first entry in every column gives the name of the sensor. All datasets are zipped into one file (data.zip).\r\n\r\nAdditionally attached is configuration data (Configuration.pdf) for the sensor fusion approach that was used to classify the datasets.\r\n\r\nFor more information please contact the uploader.\r\n"}],"_id":"13808","keyword":["sensor data","sensor defect"],"status":"public"}]