Fault Diagnostics and Prognostics
FDPTM is health monitoring software for rotating machinery using wireless sensors. The software tool consists of the following modules: 1) Input module for acquiring accelerometer, voltage, and current data; 2) Health monitoring (HM) tool; 3) Output module for displaying health index. If the system health deviates from the normal status, the health index will increase.
Video Demos:
1. Wireless Monitoring of Rotating Machinery
Our software tool consists of the following modules: 1) Input module for acquiring accelerometer data; 2) Health monitoring (HM) tool; 3) Output module for displaying health index. The basic idea in the HM tool is to use the fault free data to get a system model. If the system health deviates from the normal status, the health index will increase. The higher the vibration level, the larger the health index will be.
Software demo: The fault cases include normal, 5 g weight, 10 g weight, etc. Data collected at different cases were fed into the tool. The health indices were computed and displayed.
Real-time experiment demo:
2. Bearing Prognostics
An adaptive prognostic tool for bearing was implemented. The on-line learning capability and no historical data requirement are two advantages of the investigated approach. Because the lifetime model parameters are updated on-line using the latest diagnostic information, the remaining useful life (RUL) prediction performance is highly accurate. The approach could be applied in real-time which makes it feasible for use in industry. Actual bearing data were used to demonstrate the efficacy of the approach. The prototype is running in Matlab. We plan to develop a real-time tool in the near future.