Prognostic Health Management

(PHM)

D2K Modern PHM System Architecture

PHM Systems are evolving to meet higher expectations.
What should PHM Systems do?

· Determination of Health and its impact on system functions

· Monitor early warning of incipient failures

· Predictions of Remaining Useful Life

· Leveraging of advanced “reasoners”

· Signal processing for event detection

· Algorithms for event correlation and sensor fusion

· Expert Systems and rule-based architectures

· Advanced neural and statistical classifiers

· Real-time state estimators

· Model-based Reasoning

· Supervisory-level intelligence / logic

· Estimation and understanding of system state within operational context

· Decision support to assist operators in maintaining operational availability

· Optimize scheduling of maintenance and corrective actions according to the

principals of condition-based maintenance

D2K Real-time PHM System Data Flow

How have PHM Systems performed?

1. Expensive

2. Often ill specified

3. Often an afterthought - considered very late in design cycle

4. Excruciating test and validation cycles

5. Questionable performance

How should PHM Systems optimally be designed?

· PHM System Requirements need to be vetted early in the design cycle

· RCM focused Design Methodology should be followed

· Design tools should be leveraged that produce details for optimal sensor suite and location, FMECA, expected usage, maintenance actions and scheduling

· Need to analyze fault detection early in anticipation of onboard prognostics
requirements

· Need to link failures to detectable events across subsystems, and diagnosis to maintenance and corrective actions

· Onboard hardware and software architectures should compliment and support integration with PHM data