Student Projects
Contact Information
University: Korea Maritime University
Team Member(s): Chang-hwan Jin, Gi-woo Jeong, Dong-kee Oh, Hyun-ji Noh
Faculty Advisors: Prof. Gyung-suk Kil
Email Address: dancar1412@nate.com
Country: Republic of Korea
Project Information
Title: Lightning Warning System using an Electric Field Mill (EFM)
Description:
This project deals with the development of lightning warning system using an Electric Field Mill and LabVIEW device. Lightning Warning System can forecast the possibility of lightning strike. This system plays an important role in protecting human and devices from Lightning strike.
Products.
LabVIEW 2010 DS2 ver. , DAQmx , Touch panel module, DAQ-USB6212
The Challenge:
- Ligtning Warning system using a weather forecast type picture and electric field intensity graph
- An all-time diagnosis system established using portable EFM and touch panel PC.
- Client PCs can tansmit data to server PC.
The Solution:
>Background
Lightning causes serious damages to electrical power systems, buildings and human. For the last decades, such damages occurred not only on the ground but on flights and ships as well due to lightning strikes. Many techniques related to lightning protection have been researched. A good example solution is to forecast the occurrence of lightning by the measurement of ground-level electric field intensity. With this background, we proposed a Lightning Warning System(LWS) using an Electric Field Mill(EFM).
Fig.1 Example damages caused by lightning strike
Fig. 2 Prototype EFM
Fig. 2 shows a configuration of the prototype EFM our team made. The EFM is based on electrostatic induction method and consists of two vanes ; a sensing vane which is fixed and periodically exposed to electric field, and a rotating vane to shield electric field. The sensing vane collects electric charges and transfer to the amplifier via RC integrator. The rotating vane is driven by a brushless DC(BLDC) motor to acquire long life of the EFM function. The speed of the rotating vane is monitored by a photocoupler and is controlled constantly by a DAQ.
>Calibration
We carried out a calibration experiment to know the electric field intensity from the measured voltage signal by the EFM. Figure 3 shows the calibration setup for the EFM. Sensitivity of the EFM was calibrated at 0.85[V/kV/m] to estimate electric field intensity up to 35[kV/m].
Fig. 4 EFM's characteristic graph
>Software
Fig. 5 System configuration
-Client
(a) Fabricated touch panel PC
(b) Client VI's front panel
Fig. 6 Client Divice
-Server
Server VI shows received data from each client device and location on the map as shown in Figure 7. Also, picture rings on Figure 8 change depending on electric field intensity.
Fig. 7 Front panel of the server VI's
Fig. 8 Lightning warning level and picture ring
>Measurement
We installed the EFM at five locations as shown in Figure 9.
Fig. 9 Installation of EFMs
We acquired data during one month. An example is shown in Figure 10. Electric field intensity is about 2.5kV/m on sunny day, and cloudy day is higher than 15kV/m.
(a) sunny day
(b) Cloudy day
Fig. 10 Changes of electric field intensity
>Conclusion
We proposed a LWS which is composed of electric field milland operating system based on NI-DAQ and LabVIEW program. It is expected that the LWS can predict an occurrence of lightning and cope with lightning damages in areas.
>Video
