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ISU researchers, Vermeer team up to study machine wear and tear

TAGS: Equipment
Tyler Harris Vermeer machine in field
NEXT STEPS: ISU researchers will assist Vermeer in validating and implementing the machine health monitoring tool on some of the Vermeer machines.
Project to develop methods to detect machine faults and automate machine health monitoring.

Issues caused by wear and tear on rotating machinery could be easier to detect and predict because of a research partnership between Iowa State University and Vermeer Corp.

Vermeer makes the iconic yellow iron seen on industrial job sites and farm fields worldwide. Headquartered in Pella, Iowa, the company has manufacturing facilities and regional offices around the world. Its products are used in the agriculture, fluid management, landscape, pipeline, recycling, surface mining, technology solutions, tree care, utility installation, vacuum excavation and wood waste industries.

Chao Hu, ISU assistant professor of mechanical engineering, and his team of student researchers have been integral in this two-phase project, which began in September 2019. During the project’s first phase, the researchers focused on developing a rotor balancing method, capable of detecting and correcting an unbalance in a rotor-bearing system. Unbalance occurs in these systems when the center of mass, or gravity, of a rotor deviates from its axis of rotation.

“Many of the machine faults and failures are caused directly or indirectly by excessive vibrations generated due to unbalances in rotor systems,” Hu says. “Hence, it is of critical importance to monitor such vibrations and reduce them through timely, accurate and cost-effective balancing when a machine operates in the field.”

Engineering concepts used

The researchers relied on mechanical engineering concepts and methods, such as design of bearing and shaft components during this initial phase. Hu, who teaches these concepts and methods, says this knowledge was helpful in understanding the operating principles and characteristics of the rotor-bearing system. The research team also applied concepts of machine health monitoring to the algorithm development for rotor balancing.

Mechanical engineering Ph.D. students Nazli Javadi Eshkalak and Hao Lu, as well as a handful of undergraduate students, contributed to this first phase. Eshkalak conducted a literature review to get better insight on shaft balance monitoring and the methods used to detect and correct shaft unbalance.

“I tried to develop an algorithm which could detect whether or not the rotating shaft was unbalanced and consequently could specify the correction weights that were required to be placed on the rotor to minimize the initial vibrations of the rotor system,” Eshkalak says, adding that the developed algorithm was verified by conducting experiments on a test stand at the Wind Energy Systems Laboratory on the ISU campus. The test stand had been designed and built by the Vermeer team.

Ready for next phase

During Phase 2, the researchers will extend the findings from Phase 1 to other types of machine faults, with the hope of developing an automated, field-deployable tool for onboard machine health monitoring.

“The basic idea of this tool is to process and analyze, in almost real-time, sensor data collected from operating machines to provide transparency to machine health and achieve near-zero breakdown performance,” Hu says.

Eshkalak again contributed to Phase 2 by reviewing applicable literature; this time with the help of mechanical engineering Ph.D. student Adam Thelen, who was an undergraduate student during the early research for this project.

“To detect failures before they occur, we need to understand some fundamental physical properties of the rotor as they relate to common failure modes,” Thelen says. “Our goal is to combine knowledge of the physical properties of the rotor with real-world data to aid in diagnosing faults.”

 “The uniqueness of this type of project lies in the synergistic integration of data science and traditional [mechanical engineering] that creates research and development opportunities to develop data-driven decision-making technologies that help improve the competitiveness of the manufacturing industry,” Hu says.

Carey Novak, project manager for ISU’s Center for Industrial Research and Service, is also involved in this project by serving as the liaison between industry partners and faculty and students from ISU’s College of Engineering. One way CIRAS helps smooth the path for companies to grow is by matching them with the correct expertise for research at Iowa State. Novak has been working specifically with Hu in recent years on various company-sponsored projects.

“Dr. Hu’s group is advancing the science of machine learning and are producing great journal and conference articles from their research, part of which is supported by NSF,” Novak says. “But there are also potentially very significant commercialization opportunities in using machine learning for monitoring and predicting the health of industrial machines and equipment.”

Support from Vermeer

In addition to the support from the students and faculty involved, engineers from Vermeer have contributed to the project. Steve Daining, a senior project engineer for Vermeer and a mechanical engineering graduate of Dordt College in Sioux Center, Iowa, overseas Vermeer’s Power Systems and leads the collaboration with ISU on this project.

“There is an expectation from our customers that data should equip them to operate more productively and maintain their machines more reliably. Our goal was to make a proof of concept that demonstrated that data could protect rotating working tools at the core of many Vermeer machines,” Daining says, adding that early on, both ISU and Vermeer understood the common value in placing a high priority on development rather than focusing on research.

“The test stand allowed the ISU team to develop and test algorithms on a scaled system and allowed Vermeer to easily transfer that work into a full size prototype. The delivery of operational software was an important measure of success,” Daining says.

The next step will be for the ISU researchers to assist the Vermeer team in validating and implementing the machine health monitoring tool on some of the Vermeer machines. The research team aims to have the projected wrapped up by August.

Fetty is a communications specialist with ISU’s College of Engineering.

Source: Iowa State University College of Engineering, which is responsible for the information provided and is wholly owned by the source. Informa Business Media and its subsidiaries aren’t responsible for any of the content contained in this information asset.

 

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