Dust explosions can be among the most dangerous and costly workplace incidents. Dust builds up in agricultural, powder-handling, or manufacturing settings, causing hazards to employees and posing the risk of exploding.
Researchers at Purdue University have developed an image- and video-based application using OpenCV algorithms that detect explosible suspended dust concentration. The app uses a camera or a video recording device to image and determine suspended dust and to accurately distinguish it from normal background noise.
“Determining suspended dust concentration allows employers to take appropriate safety measures before any location within the industry forms into an explosive atmosphere,” said Kingsly Ambrose, an associate professor of agriculture and biological engineering who leads the research team. “I believe this technology could help prevent dust explosions and will be of great benefit to the industry.”
Ambrose said current technology for detecting dust levels is inconvenient because it is expensive, difficult to install in a workspace and separates dust matter into multiple filters that must be weighed and further manipulated for analysis.
Ambrose said that in testing, the algorithm successfully recognized 95% of sawdust and 93% of cornstarch particulates in the air.
“This technology is unique because it is easy to use without extended training, location independent and does not require permanent installations,” Ambrose said.
The Purdue team’s work is published in the Journal of Loss Prevention in the Process Industries.