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WVU making progress in mine safety research

Portraits of mine safety researchers Kecojevic, Kulathumani, and Nimbarte

A trio of interdisciplinary researchers at West Virginia University are making headway in the tedious battle against surface mining industry injuries and fatalities.

MORGANTOWN, W.Va.—

“Although numerous technological advances have been made in the area of mine safety, injuries persist in surface mining operations due to equipment size, mine topography and operational complexity,” said Vladislav Kecojevic, professor of mining engineering. “Our research is progressively addressing this issue.”

Over the past three years, Kecojevic, Vinod Kulathumani, associate professor of computer science and electrical engineering, and Ashish Nimbarte, assistant professor of industrial and management systems engineering, have designed and developed a two-part integrated sensing and communication system that helps prevent accidents due to equipment collisions and drive fatigue and distraction.

Joining the faculty on the project are computer science graduate students Ajay Kavuri, Shashank Sabniveesu, Rahul Kavi, R. Rohit and Masahiro Nakagawa, and mining engineering graduate student Prakash Bishleshan.

The first part of the system is a proximity-warning function that uses low-power radio waves to alert machinery operators to workers and vehicles less than 10 meters away. The system does not have line of sight restrictions or blind spots, unlike ultrasonic sensors and cameras. A global positioning system integrated with Wi-Fi radios in ad-hoc mode was also designed to give warning about vehicles approaching from distances over 10 meters.

To combat driver fatigue, the system uses a combination of infrared cameras, accelerometers and wearable electroencephalogram sensors to detect the onset of behaviors associated with fatigue. Any deviation in driver characteristics, like a change in blinking patterns or variations in EEG data, can be used to trigger fatigue alert. The research team also developed MapMyTruck, a cloud-based logging framework to collect long-term data from GPS and other sensors that can record and analyze near-miss data.

The system has been tested at the Red Hills Mine in Ackerman, Mississippi, and Liberty Fuels Mine in DeKalb, Mississippi, with positive results.

“In testing, we’ve found that the system functions correctly and does have the ability to make a substantial difference in the safety of surface mine workers,” said Kecojevic. “Now, these test mines will continue using these systems so we can obtain long-term data to gage the effectiveness and reliability of the system.”

The next phase of the project focuses on the development of techniques to quantify the distraction posed by surface mining equipment consoles and the drowsiness experienced by drivers, and use that data to assess and mitigate the risk of injuries in surface mine operations.

“The outcomes of the next phase of our research are expected to help both understand the risks and design corrective actions to address them,” said Kecojevic. “They can also be used to help develop personalized work shifts for drivers and to design better response strategies upon detection of drowsiness in drivers. In contrast to subjective assessments of comfort levels with on-board consoles, the outcomes of driver distraction analysis will provide quantitative insight into shortcomings of console placement and design.”

Kecojevic is quick to add that the technology has applications to all forms of surface mining, including coal, metal and nonmetal.

The research is funded by a $742,000 award made by the Alpha Foundation for the Improvement of Mine Safety and Health.


-WVU-

bmd/6/29/16

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