Alfred University to host short course on machine vision

From left, Alfred University students Jannatun Naiem, graduate student in electrical engineering, Momodou Wurry Jallow, sophomore electrical engineering major, Naimul Haque, graduate student in electrical engineering, and Saron Mindaye, sophomore computer science major, with ceramic insulators on display in the McMahon Engineering Building. The students are working on artificial intelligence-related projects in the Inamori School of Engineering this summer, with Haque and Naiem helping prepare for an EPRI short course in early September on machine vision, a technology which uses AI to locate and assess damage to electrical power line insulators like the ones shown in the photo above.

Alfred University's Inamori School of Engineering will host a short course in September that will train students and faculty on the use of artificial intelligence (AI) technology to identify and assess damage to electrical power systems. Students completing the course will increase their internship opportunities and become more attractive to employers in the electric utility sector.

The three-day short course on machine vision will be provided by EPRI, an independent, non-profit energy research and development organization, on Sept. 3, 4, and 5 on the Alfred University campus. It is the first industry-standard course among other EPRI short courses that will be offered as part of a workforce development initiative at Alfred University supported by a $466,853 grant from the New York State Energy Research and Development Authority (NYSERDA). EPRI is also providing the University access to resources from GridED, EPRI's workforce development initiative. GridEd seeks to develop and train the next generation of power engineers and data scientists so that they can help shape the electric grid of the future by anticipating and fulfilling the needs of changing requirements.

In addition to the resources provided by EPRI, the NYSERDA funding will support student internships in the electric utility field and facilitate the acquisition of a microgrid control center and a DERs (distributed energy resources) command center to be used as a training resource. As part of this workforce development program, Alfred University has also received $2,786,000 from GE Vernova in power grid planning and operations software - resulting in the launch of the GE Vernova Advanced Power Grid Lab.

Xingwu Wang, professor of electrical engineering at Alfred University is one of four faculty from the Inamori School of Engineering serving as researchers on the NYSERDA project. He said that the short course offered in September will train students on the use of machine vision, a technology that utilizes AI to give industrial equipment the ability to "see" what it is doing and make rapid decisions based on what it sees.

The most common uses of machine vision are visual inspection and defect detection, positioning and measuring of parts, and identifying, sorting, and tracking products. The technology makes use of high-speed cameras that automate visual inspection. As it applies to electrical utilities, machine vision technology makes use of cameras, which provide images of utility equipment, such as pole-mounted insulators, to determine the location and extent of damage to that equipment. Images are transmitted to a computer database, where they are analyzed using AI programming, which compares the damaged equipment (power line insulators, for example) with pristine equipment to determine the location and extent of the damage.

Automation provided by machine vision technology is needed due in part to increased extreme weather events and a decrease in the number of utility workers who have traditionally performed detection and assessment of damaged electrical power infrastructure. Power lines can contain hundreds of insulators and in the event of a power outage, it could take several hours to locate the damaged equipment causing the interruption.

"Repairs can be completed much more quickly" using machine vision technology, Wang said. "Regulations require that utilities fix problems right away. The utilities have to rely on AI to meet those demands."

Over the three-day machine vision short course, EPRI will teach the technology to students and faculty at Alfred University. The program will also be open to existing workers in the electrical utilities sector. Initially, over the first half-day of the course, a minimum of five Alfred University faculty from the electrical engineering, renewable energy engineering, mechanical engineering, computer science, and materials science and engineering programs will be trained on machine vision technology.

There will be an estimated 22 students enrolled in the course. Two representatives of EPRI will lead the course, with the trained Alfred University faculty serving as teaching assistants. Those faculty will in turn be able to train other Alfred University faculty to lead future short courses. "The idea is to propagate the program outward," Wang said.

Students completing the course will be issued certification from EPRI. "Students will be better equipped to secure internships in the electrical industry. It will give them the knowledge, experience, and skills they need when looking for jobs," Wang noted.

On-line registration is available for students over the summer. Thus far, Wang said, seven students have expressed interest in enrolling in the machine vision short course. In addition to Alfred University students, the EPRI short courses will also be offered to employees of Avangrid, an energy services and delivery company whose subsidiaries include regional power providers Rochester Gas and Electric (RG&E) and New York State Electric and Gas (NYSEG), as well as other regional electrical utilities.