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---
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