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Purdue dust explosion.jpg Kingsly Ambrose/Purdue University
Researchers at Purdue University have developed an image- and video-based application using OpenCV algorithms that detect explosible suspended dust concentration.

Real-time imaging can help prevent deadly dust explosions

App uses camera or video recording to determine suspended dust, which could allow facilities to take appropriate safety measures.

Dust explosions can be among the most dangerous and costly workplace incidents, according to Purdue University, because dust that builds up in agricultural, powder handling or manufacturing settings can be hazardous to employees and pose explosion risks.

Researchers at Purdue University have developed an image- and video-based application using OpenCV algorithms that detects explosible suspended dust concentrations, the university announced.

Their work was published in the Journal of Loss Prevention in the Process Industries.

The app uses a camera or a video recording device to image and determine suspended dust as well as to accurately distinguish it from normal background noise, the announcement said.

"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, a Purdue associate professor of agricultural 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."

He 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 noted 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," he said.

Ambrose and the team worked with the Purdue Research Foundation Office of Technology Commercialization to patent the technology. They are looking to license it and are seeking collaborators for further development.

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