Electronic System Condition Monitoring and Prognostics

Technology #13122

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A diagram of an exemplary embodiment of a system in accordance with the present teachings.A list of sensors that may be available for providing data to an exemplary implementation of a system in accordance with the present teachings. Illustrates a remote vehicle having a display indicating a target electrical system and the predicted condition of various aspects of the target electrical system's condition.
Categories
Inventors
Professor Nicholas Roy
Department of Aeronautics and Astronautics, MIT
External Link (groups.csail.mit.edu)
Michael Rosenstein
Home Robots
Bryan Adams
Home Robots
Managed By
Christopher Noble
MIT Technology Licensing Officer - Clean and Renewable Energy
Patent Protection

ELECTRONIC SYSTEM CONDITION MONITORING AND PROGNOSTICS

US Patent 8,200,600

Applications

This technology monitors and predicts failures of electronic systems such as mobile robots.

Problem Addressed

Many current technologies aim to create extremely robust systems that minimize potential errors. This approach is different because it aims to create a safety net that predicts and mitigates failures as they occur to prevent the system from ever becoming unusable.

Technology

This system is comprised of a component model, an inference engine based on the component model, and an action selection component that selects an action based on an output of the inference engine. The current application is a mobile robot. The data collected to build the component model is dependent on the application. However, for the mobile robot the data relates mainly to the battery (i.e. voltage, current, temperature, etc; a more exhaustive list is in the images). After collecting data on the basic functionality of the system and at least one potential failure, the component model is created. This model along with real-time sensor data is fed to the inference engine, which makes predictions about the power system and the likelihood of failure. The final step is the action selection component, which can mitigate potential failures or create new data to improve prediction accuracy. Information on the state of the system, likelihood of failure, and preventative actions can be displayed in an interface as pictured in the images.

Advantages

  • Mitigates and prevents failures in an electronic system
  • Requires a less robust electrical system
  • Requires less maintenance than traditional electronic system¬†