Catherine Mary Graichen

Algorithm to automatically detect abnormally long periods of inactivity in a home

An algorithm has been developed to automatically construct individual models of normal activity within a home using motion sensor data. Alerts can be generated when a period of inactivity exceeds a normal length for a particular residence. Alerting frequency has been optimized on a total of 650 days of real data from four homes of seniors who live independently. Results suggest that an inexpensive system that does not require the occupant to push any buttons or wear any devices could nonetheless alert within hours if a senior is unusually inactive. Further, such algorithms may facilitate widespread deployment of smart home technology to persons with different behavior patterns and home layouts by using automatic learning in place of potentially tedious manual configuration.

Unobtrusive vital signs monitoring with range-controlled radar

Researchers at General Electric have developed a prototype demonstration system that can identify motion and measure breathing and heart rate in periods without general body motions using a range-controlled radar device, similar to motion detectors available in home security systems. With continuous monitoring of the activity and physical vital signs, warning criteria can be used to identify potential crises augmenting existing observational systems without requiring the observed individual to wear or attach any special devices. This has potential applications in correctional facilities to complement observation for inmates at risk of suicide. It has healthcare applications where attaching traditional vital sign monitoring equipment is difficult such as for neonatal or burn patients.

Case-Based Reasoning Approaches for Gas Turbine Trip Diagnosis

Effective maintenance, repair and design improvements of gas turbines require the classification of turbine automatic shutdown events into actionable categories. In particular, analysis is required at two distinct points in the life cycle of a shutdown event. The first evaluation is at the time of the shutdown when an initial assessment of the cause and the appropriate action must be decided as quickly as possible to return the turbine to service. At the time of the event, the primary sources of data are information collected from the sensors and control system. A second assessment is often performed as a post-event evaluation using additional information to validate the cause. General Electric created Case-Based Reasoning (CBR) tools to perform these classifications automatically. The first CBR tool, which works at the time of the event, was deployed in 2004. The second CBR tool was placed in operation in 2006.Copyright

Adding code generation to develop a simulation platform

Efficient and accurate control technologies require extensive simulation capabilities to validate the control software and demonstrate the impact on the business and equipment. To create a platform for rapid development and simulation of complex dynamic models, the authors and their colleagues have designed an object-oriented architecture. A portion of the architecture framework is constructed using code generation based on XML component definitions. This paper describes the key aspects of the architecture of the control simulator platform and its code generation capabilities. The simulation platform consists of defining a collection of components represented by differential equations, the capability to select, configure and interconnect components, and the ability to solve the coupled set of equations. The code generation is custom-built, however, the generated code results in more consistency and improved reliability by eliminating error prone steps and allowing the simulation engineer to focus on component mathematical description. As the number of components that are generated increases, the investment in a custom-built code generation is quickly realized by significantly reducing the amount of time required to create or update the code template for each component. The paper also discusses the importance of handling updates as well as the initial creation of code files. The techniques leveraged within this project have been learned through the use of other code generation tools, including GUI development tools. In particular, care has been taken to minimize the accidental loss of manually introduced code and handle version updates of the code generator. Our team is using this framework to develop simulation tests for power plant optimizations and have plans to add custom code generation to other areas of the platform.

Mapping heterogeneous information to facilitate fusion for improved lifing estimates

Abstract - This paper describes a method for individualized equipment component lifing estimates. The basic idea of individualized lifing estimate is to not only take into account age-based population distributions (as expressed by age Weibull curves) but also other factors that could potentially influence the remaining life of a equipment component. For example, these additional factors might include usage data, error code information, overhaul test results, replacement parts information, and others. Integrating this information produces a more refined lifing estimate for equipment components compared to an estimate based on age alone. However, measurements and otherwise recorded data are rarely a direct indicator of how much the lifing estimate should be adjusted. Rather, these data were originally meant to serve other goals. In addition, data sources may be highly heterogeneous in nature, and may provide conflicting information. To allow a unified representation we propose in this paper ontological information modeling which is supplemented by mapping functions that allow inferencing from data sources to the quantity of interest. We then fuse the output from the different information sources and finally compare the resulting Weibull distribution with the age-based Weibull distribution. Keywords: Information fusion, decision fusion, lifing, Weibull, heterogeneous information.