System and Method for Diagnosing the Nature and Magnitude of Faults within Dynamic Systems
Fault detection and diagnosis is essential across diverse industries. They increase safety and reduce costs, replacing current scheduled-based maintenance strategies which cost billions yearly.
Dr. Nataraj’s fault detection system invention provides a software-based method for diagnosing the nature and magnitude of faults within dynamic mechanical and electrical systems. The software uses measured data from already existing fault detection sensors and computes, with high accuracy, the possibility that there is a defect, such as a bearing defect or crack shaft defect, in the system; the algorithm also estimates the magnitude of the fault. It accomplishes this using mathematical analysis, nonlinear dynamics techniques, time series analysis, signal processing and machine learning. The software has been tested in multiple mechanical systems and performed with near perfect accuracy. The software can be generalized to a wide variety of mechanical and electrical systems. Not only will this make systems such as engines and motors safer, it will also cut maintenance costs significantly by providing more detailed information noninvasively than current systems allowing inspections to occur when needed rather than on an automated schedule.
Dr. Nataraj offers a superior solution to fault detection and diagnosis at a much lower investment cost than current methods, such as regularly scheduled inspection. All that is required is small computer to connect to already existing fault diagnostic sensors.
- Unique algorithm that utilizes mathematical analysis, nonlinear dynamics techniques, time series analysis, signal processing and machine learning to diagnose faults in mechanical systems.
- Compatible with sensors already present in many mechanical sensors.
- Highly accurate, with 100% accuracy in laboratory setting, making machinery much safer by providing a higher confidence level than exists currently.
- Generalizable to many different mechanical and electrical systems.