@misc{13808,
  abstract     = {{

Thirteen 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:

    Sensor Drift: 1‰/hour (data_drift_0_001.csv), 2.5‰/hour (data_drift_0_0025.csv), 5‰/hour (data_drift_0_005.csv)
    Sensor Offset: 1°C Offset (data_offset_1.csv), 2°Offset (data_offset_2.csv), 5°Offset (data_offset_5.csv)
    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)
    Sensor Noise: 10 dB SNR (data_noise_10dB.csv), 0 dB SNR (data_noise_0dB.csv)

The 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).

Additionally attached is configuration data (Configuration.pdf) for the sensor fusion approach that was used to classify the datasets.

For more information please contact the uploader.
}},
  author       = {{Ehlenbröker, Jan-Friedrich and Mönks, Uwe and Lohweg, Volker}},
  keywords     = {{sensor data, sensor defect}},
  publisher    = {{Zenodo}},
  title        = {{{Typical Sensor Defects Dataset}}},
  doi          = {{10.5281/ZENODO.56358}},
  year         = {{2016}},
}

@misc{13823,
  abstract     = {{
Two datasets of sensor values, with each dataset including one defect sensor that delivers incorrect values. The datasets where gathered during tests in a hazardous material storage demonstrator.

The datasets are given as comma-separated values in text files. The first line in each file holds time stamps, while the following lines hold the sensor values. The first entry in every line gives the name of the sensor.

The first dataset (data_scenario_1.csv) was recorded under normal operating conditions, with the sensor Temperature_Inside_8 delivering incorrect values. In the second scenario (data_scenario_2.csv) there is a leakage of fluid inside the hazardous material storage. At the same time the sensor Smoke_Inside_0 delivers incorrect values.

Additionally attached is configuration data (Configurations.pdf) for the sensor fusion approach that was used to classify the datasets.

For more information please contact the uploader.
}},
  author       = {{Ehlenbröker, Jan-Friedrich and Mönks, Uwe and Lohweg, Volker}},
  keywords     = {{sensor data, sensor defect}},
  publisher    = {{Zenodo}},
  title        = {{{Sensor Defect Detection Datasets With Configuration}}},
  doi          = {{10.5281/ZENODO.48728}},
  year         = {{2016}},
}

@misc{13822,
  abstract     = {{ 

Two datasets of sensor values, with each dataset including one defect sensor that delivers incorrect values. The datasets where gathered during tests in a hazardous material storage demonstrator.

The datasets are given as comma-separated values in text files. The first line in each file holds time stamps, while the following lines hold the sensor values. The first entry in every line gives the name of the sensor.

The first dataset (data_scenario_1.txt) was recorded under normal operating conditions, with the sensor Temperature_Inside_8 delivering incorrect values. In the second scenario there is a leakage of fluid inside the hazardous material storage. At the same time the sensor Smoke_Inside_0 delivers incorrect values.}},
  author       = {{Ehlenbröker, Jan-Friedrich and Mönks, Uwe and Lohweg, Volker}},
  keywords     = {{sensor data, sensor defect}},
  publisher    = {{Zenodo}},
  title        = {{{Sensor Defect Detection Datasets}}},
  doi          = {{10.5281/ZENODO.34511}},
  year         = {{2015}},
}