This Small Business Innovation Research (SBIR) Phase I project aims to develop an innovative integrated wear debris sensor for condition health monitoring of rotating and reciprocating machinery via detecting metallic and nonmetallic wear debris in the machinery?s lubrication oil. Today?s online debris sensors can provide only limited information on the progression of machine wear or do not have in-situ online capability. This Phase I project will focus on building a laboratory prototype to demonstrate the proof-of-concept high-throughput detection, differentiation, characterization, and counting of nonmetallic, and metallic (ferrous and non-ferrous) debris ranging from 20ìm to 150ìm (which are indicative of machines? wear status) in real time. The integrated sensor will consist of 1) an ultrasonic sensing unit with a unique flow recess design that accurately detects all metallic and non-metallic debris, and 2) an inductive Coulter counting sensing unit that detects and differentiates ferrous and non-ferrous metallic debris. It is anticipated this sensor is able to accurately measure wear debris size and concentration of each type, and thus provide information for conditioning based maintenance and life prognosis of a variety of high speed rotary machinery including rotorcraft transmissions and turboshaft engines.
The broader impact/commercial potential of this project is an innovative high throughput oil debris sensing technology that provide advance warning of sudden catastrophic failure, facilitate better maintenance scheduling, and significantly reduce the cost of machine operation. The high throughput and high sensitivity of the sensor, along with its low cost and compact size, makes it an ideal instrument for real-time condition monitoring and life prognosis for a variety of machinery such as bearings, gearboxes, and turbomachinery, and thereby have broader impacts on and commercial potentials for the transportation, manufacturing and military industries. It is a powerful complement to existing offline oil wear debris analysis. The proposed research will form the scientific foundation for the development of advanced sensors systems for micro/nanoscale particle sensing. In particular, studies of particle sensing in a nonconductive, high viscous environment are poised to have a transformative impact on monitoring new soft materials processing involving micro/nano particles, and the development of sensors for detecting metallic and dielectric particle contamination in nonconductive materials and environments.
Oil analysis has become commonplace for many commercial and military applications, and efforts have been put forth to bring traditional oil analysis procedures into the real time realm. Real time monitoring is a vital tool that can provide timely information concerning wear of bearings, gears, and other components of machinery systems. This information may be used to provide warnings of impending part or system failures, and/or the need for maintenance actions. An effective oil condition monitoring system allows lubricants to be used to their fullest potential while minimizing equipment downtime, resulting in increased operational readiness, cost savings, and productivity. Akron Air Materials (AAM) has successfully developed and demonstrated a novel Oil Debris Monitor that provides significant improvements in the real-time detection of wear debris in lubricating oils. The key elements of the AAM Oil Debris Monitor are an ultrasonic pulse sensor and an integrated inductive planar coil/coulter counter. AAM has demonstrated that the ultrasonic pulse sensor device detects and counts all debris particles including metallic and non-metallic in addition to air bubbles. The inductive coulter counting device detects and differentiates between ferrous and non-ferrous particles. Thus the AAM integrated sensor system: ? Detects the total number debris particles in the oil, and distinguishes solid particles from air bubbles ? Differentiates between metallic and non-metallic debris particles ? Further differentiates between ferrous and non-ferrous metallic debris particles The AAM device utilizes a flow recess structure to channel all wear debris through the acoustic focal region ensuring that all debris are accurately counted and sized. The inductive Coulter counting sensor detects and counts all metallic debris (ferrous and nonferrous) based on an inductive Coulter counting principle. By combining the results from the two sensing components, the sensor is capable of differentiating and detecting non-metallic debris, ferrous metallic debris and nonferrous metallic debris. The phase I research model has successfully detected wear debris as low as 40 μm. Commercialization of the Akron Air Materials Oil Condition Monitor will facilitate optimized maintenance scheduling, thereby significantly reducing the cost of machine operation. The high throughput sensitivity of the instrumentation, makes it an ideal instrument for real-time condition monitoring and life prognosis for a variety of machinery including bearings, gearboxes, and turbomachinery. By reducing maintenance and overhaul costs by 50% or more, the wind energy industry will have a far greater chance of achieving its goal of supplying 20% of the nation’s energy demand. Aircraft operators will realize operating cost reductions, leading to a corresponding reduction in fare prices. Domestic firms in all industries that rely on heavy machinery in their operations will become more competitive with overseas operations thus retaining and creating jobs. All of these results will have a positive benefit to society. Scientifically, the proposed research will form the foundation for the development of advanced sensors systems for micro/nanoscale particle sensing. In particular, studies of particle sensing in a nonconductive, high viscous environment are poised to have a transformative impact on monitoring new soft materials processing involving microparticales and nanoparticles, and the development of sensors for detecting metallic and dielectric particle contamination in nonconductive materials and environments.
