Case School of Engineering, Rockwell researchers create intelligent fluid sensor for reliable machinery operation
Kenneth Loparo's research involves design of fault detection, diagnosis and prognosis for rotating machinery
Effective lubrication systems are essential to the reliable operation of critical industrial, commercial and military machinery. Operating requirements such as temperature extremes, high load, high speed or airborne contaminants place severe demands on lubrication systems. That’s why researchers at Case Western Reserve University’s School of Engineering and their partners at Rockwell Automation have developed an intelligent fluid sensor to help insure the reliability of lubrication systems for critical machinery.
“Failure of a lubrication system can result in wasted energy, noisy operation, mechanical damage, dangerous operating conditions or even a catastrophic event,” said Kenneth Loparo, professor of electrical engineering and computer science at Case whose research, in part, involves the design of fault detection, diagnosis and prognosis for rotating machinery. “Lubrication health information may provide an early indication of problems before any mechanical damage has occurred. Continuous monitoring of fluid condition will be able to detect faults that occur between scheduled maintenance activities, and possibly avert catastrophic failures.”
A research team of Loparo, C.C. Liu, the Wallace R. Persons Professor of Sensor Technology & Control in Case’s department of chemical engineering; and Fred M. Discenzo, Dukki Chung and research staff members at Rockwell Automation’s Advanced Technology Labs in Mayfield Heights, Ohio, have developed the multi-element lubrication health sensor to continuously monitor critical fluids in machinery during operation.
The objective of this new device is to provide important fluid information to support maintenance and avoid machinery failure. For example, some pumps or gearboxes may lose lubrication due to a seal failure, or fluid may become contaminated with water or metal debris from damaged mechanical components in the machine. Under these operating conditions, continued operation under load for extended periods of time can cause severe and costly damage to the machine. Additional benefits are possible by integrating lubricating fluid information with other diagnostic and control maintenance management, operations scheduling and mission planning systems, the researchers say.
Mechanical problems are important to detect before they cause a catastrophic failure of the machine. An intelligent lubrication sensor may be able to provide an early warning of impending mechanical problems in the machine resulting from excessive wear. This is particularly important for electric motors, where most of the reported failures are the result of a bearing failure. A large number of these bearing failures are the result of lubrication and contamination problems, Loparo says.
The intelligent fluid sensor is comprised of a “suite” of electrical and electrochemical sensor elements, fabricated using microelectromechanical (MEMS) techniques and includes sensor control logic, signal processing and sensor fusion algorithms to analyze the sensor data and make a decision about lubricant health. The researchers report that preliminary test results in industrial and aircraft fluids show excellent compatibility with laboratory test results.
The sensor has been tested in industrial and aircraft fluids, including fluids degraded in a controlled manner, and fluids degraded due to industrial machinery operation and aircraft flight operations. The fluids tested include gear oil, mineral oil, bearing grease and hydraulic fluid.
The multi-element fluid sensor utilizes several different sensor elements fabricated on a single substrate, which is a single crystal of a semiconductor used as the basis for a host of integrated circuit devices, says Loparo. Each individual sensor element provides important information related to the condition of the fluid. The sensor elements consist of a temperature sensor, conductivity sensor, a three-electrode electrochemical sensor, and a two-electrode acidity (TAN) sensor. Additional MEMS sensor components include elements to measure fluid viscosity and density.
The integration of multiple sensor elements on a single substrate and sensor data processing using sensor fusion techniques will provide for a robust sensor that can be extended to determine important fluid and system diagnostic information, the researchers say. Sensor development is targeted to provide a low-cost, compact intelligent sensor element that may be readily embedded in machinery to provide continuous monitoring of critical fluids.
“Sensor design and fabrication techniques utilize established microelectronic and lithographic methods and should result in a low-cost, small sensor,” Loparo said. “We feel that industry has much to gain from employing these types of low-cost sensors in machinery. There is a strong motivation among industries to reduce maintenance, repair and operations costs, and further, business models and concern for the environment and worker safety are driving many organizations to do whatever is necessary to avoid machinery failures.”
About Case Western Reserve University
Case is among the nation's leading research institutions. Founded in 1826 and shaped by the unique merger of the Case Institute of Technology and Western Reserve University, Case is distinguished by its strengths in education, research, service, and experiential learning. Located in Cleveland, Case offers nationally recognized programs in the Arts and Sciences, Dental Medicine, Engineering, Law, Management, Medicine, Nursing, and Social Work. http://www.case.edu.