Henan Bangxin Anti-corrosion Materials Co., Ltd. specializes in the production of lightning warning systems.

Depending on the requirements of the usage scenario, different installation methods can be flexibly adopted: fixed lightning warning systems, vehicle-mounted lightning warning systems, and portable lightning warning systems.

Lightning monitoring and warning refer to the use of observation data such as lightning positioning, radar, satellites, ground electric fields, and sounding, through multi-data fusion applications, statistical analysis, near-term extrapolation, and numerical forecasting techniques, to identify, track, and forecast warnings for areas where lightning may occur or has already occurred. Real-time monitoring of lightning activities and graded warnings for lightning approaching key locations have been implemented to effectively prevent and reduce lightning hazards.

Using single-station electric field observations makes it difficult to estimate the location of thunderstorm clouds. The warning area and advance warning time are very limited, and there are some uncertainties. Additionally, since ground atmospheric electric field measurements are greatly affected by the installation environment, especially in urban areas, it is difficult to find ideal installation conditions. Therefore, the average electric field warning indicators used at different sites vary and require site-specific calibration or empirical criteria based on long-term observations.

For passing thunderstorms, the effective response range of electric field meters is limited, which greatly restricts the advance warning time (though this can be supplemented by networked observations or other methods such as radar, satellites, and lightning positioning). For newly formed thunderstorm clouds within the observation network of electric field meters, ground electric field observations can theoretically achieve excellent warning effects (using the average trend of electric field changes as a warning indicator), though this still requires validation through actual observations.