Dataset for binary classification of digital sensor signals
The dataset is composed of digital signals obtained from a capacitive sensor electrodes that are immersed in water or in oil. Each signal, stored in one row, is composed of 10 consecutive intensity values and a label in the last column. The label is +1 for a water-immersed sensor electrode and -1 for an oil-immersed sensor electrode. This dataset should be used to train a classifier to infer the type of material in which an electrode is immersed in (water or oil), given a sample signal composed of 10 consecutive values.
The dataset is acquired from a capacitive sensor array composed of a set of sensor electrodes immersed in three different phases: air, oil, and water. It is composed of digital signals obtained from one electrode while it was immersed in the oil and water phases at different times.
## Experimental setup
The experimental setup is composed of a capacitive sensor array that holds a set of sensing cells (electrodes) distributed vertically along the sensor body (PCB). The electrodes are excited sequentially and the voltage (digital) of each electrode is measured and recorded. The voltages of each electrode are converted to intensity values by the following equation:
intensity = ( |Measured Voltage - Base Voltage| / Base Voltage ) x 100
Where the Base Voltage is the voltage of the electrode recorded while the electrode is immersed in air. The intensity values are stored in the dataset instead of the raw voltage values.
## Experimental procedure
The aim of the experiments is to get fixed-size intensity signals from one electrode (target electrode) when being immersed in water and oil; labeled as +1 (water) or -1 (oil). For this purpose, the following procedure was applied:
- The linear actuator was programmed to move the sensor up and down at a constant speed (20 mm / second).
- The actuator stops when reaching the upper and bottom positions for a fixed duration of time (60 seconds).
- At the upper position, the target electrode is immersed in oil; intensity signals are labeled -1 and sent to the PC.
- At the bottom position, the target electrode is immersed in water; intensity signals are labeled +1 and sent to the PC.
- The sampling rate is 100 msec; since each intensity signal contains 10 values, it takes 1 second to record one intensity signal
## Environmental conditions
The experiments were perfomed under indoors laboratory conditions with room temperature of around 23 degree Celsius.
## Dataset structure
The signals included in the dataset are composed of intensity signals each with 10 consecutive values and a label in the last column. The label is +1 for a water-immersed electrode and -1 for an oil-immersed electrode.
The dataset should be used to train a classifier to differentiate between electrodes immersed in water and oil phases given a sample signal.