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metadata
language:
  - en
license: cc-by-nc-4.0
pretty_name: Non-thermal Plasma Parallel DBD Air Dataset
task_categories:
  - feature-extraction
  - other
tags:
  - plasma
  - dielectric-barrier-discharge
  - non-thermal-plasma
  - physics
  - time-series

Non-thermal Plasma Parallel DBD Air Dataset

Overview

This dataset contains experimental time-series measurements from a parallel Dielectric Barrier Discharge (DBD) plasma system in air at NTP. The dataset was collected using a digital oscilloscope and includes current-voltage waveforms measurements for plasma discharge characterization.

Data Acquisition

The experiments were conducted in the Physics Laboratory, Department of Physics, Kathmandu University. Measurements were recorded using:

  • Digital Oscilloscope: Tektronix TDS 2002
  • High Voltage Probe: PINTEK HVP-28HF (1000:1 attenuation ratio)
  • Current Measurement: 10 kΩ shunt resistor

All measurements were performed under controlled DBD plasma conditions in air at NTP.

Experimental Setup of the DBD System

The dielectric barrier discharge (DBD) system consists of a parallel electrode configuration placed inside a transparent polycarbonate reaction chamber. The system is designed for plasma generation in air under normal atmospheric pressure conditions. The setup includes the following components:

  • (1) Parallel electrodes for plasma generation
  • (2) Dielectric barrier sheet separating the electrodes
  • (3) Ballast resistor
  • (4) Shunt resistor used for current measurement
  • (5) High voltage probe for voltage measurement
  • (6) Oscilloscope probe for signal acquisition
  • (7) Digital oscilloscope for waveform recording
  • (8) Reaction chamber (polycarbonate enclosure)
  • (9) High voltage AC transformer (50 Hz operation)
  • (10) Ground connection
  • (11) Computer interface for data acquisition and monitoring

Geometrical and Electrical Configuration

  • Chamber dimensions: Polycarbonate (35.7 cm × 20.0 cm × 15.0 cm)
  • Electrode configuration: Parallel plate electrodes
  • Electrode material: Copper
  • Upper electrode dimensions: (7.53 cm × 4.97 cm × 0.47 cm)
  • Grounded electrode dimensions: (7.54 cm × 4.99 cm × 0.48 cm)
  • Electrode gap: 6 mm
  • Dielectric barrier: Polycarbonate plate (13.0 cm × 10.0 cm × 0.197 cm)
  • Applied voltage: 15.65 kV AC
  • Frequency: 50 Hz
  • Shunt resistor: 10 kΩ

The DBD electrode configuration was placed inside a transparent polycarbonate chamber (35.7 cm × 20.0 cm × 15.0 cm). An AC high voltage of 15.65 kV at a frequency of 50 Hz was applied across the electrodes. The separation between the upper electrode (7.53 cm × 4.97 cm × 0.47 cm) and the grounded electrode (7.54 cm × 4.99 cm × 0.48 cm) was 6 mm. The dielectric barrier consisted of a polycarbonate plate (13.0 cm × 10.0 cm × 0.197 cm). A polycarbonate sheet was inserted between the two electrodes to serve as the dielectric barrier.

The discharge was generated between two rectangular parallel electrodes. The oscilloscope probe was connected across a 10 kΩ shunt resistor for current estimation. The voltage and current waveforms were monitored and analyzed using a digital oscilloscope. In this work, a high-voltage AC supply operating at 50 Hz was used.

Dataset Structure

The dataset consists of multiple experimental conditions labeled by numerical values (100, 110, 120, ..., 220). Each condition represents a different oscilloscope division of the DBD system.

Examples

  • 100a.csv → Condition 100, run A
  • 100b.csv → Condition 100, run B
  • 110a.csv → Condition 110, run A
  • 110b.csv → Condition 110, run B
  • 120a.csv → Condition 120, run A
  • 120b.csv → Condition 120, run B
  • ...
  • 220a.csv → Condition 220, run A
  • 220b.csv → Condition 220, run B

Data Format

Each CSV file contains time-series waveform data:

Column Description Unit
Time Time seconds (s)
Voltage Applied voltage kilovolts (kV)
Current Discharge current milliamperes (mA)

Intended Use

This dataset can be used for:

  • Plasma physics analysis
  • Dielectric barrier discharge characterization
  • Time-series signal processing
  • Feature extraction from plasma waveforms
  • Machine learning on experimental physics data
  • Lissajous (Q–V) method studies
  • Electrical power and energy estimation in plasma systems

Institution

Plasma Physics Laboratory
Department of Physics
Kathmandu University, Dhulikhel, Nepal