General Electric Company

Ge Medical Systems

Mark David Osborn

Rasiklal Punjalal Shah

Vrinda Rajiv

LiJie Yu

Jieqian Cathy Chen

Piero Patrone Bonissone

Mark Edward Dausch

Catherine Mary Graichen

Mahesh Kumar Asati

Nishith Pramod Vora

Venkatarao Ryali

Daniel Joseph Cleary

Vijaysai Prasad

Sunil Shirish Shah

Ivy Wai Man Chong

Ernest Joseph Waldron

Shirley Suet-Yee Au

Amey Sudhakar Joshi

Sreevidya Sambasivan

A technique is disclosed for evaluating and monitoring performance of a heat exchanger system. Operating parameters of the system are monitored and fouling factors for heat transfer surfaces of the exchanger are determined. Trending of fouling may be performed over time based upon the fouling factors, and a model of fouling may be selected from known sets of models, or a model may be developed or refined. Fluid treatment, such as water treatment regimes may be taken into account in evaluation of fouling. An automated knowledge based analysis algorithm may diagnose possible caused of fouling based upon sensed and observed parameters and conditions. Corrective actions may be suggested and the system controlled to reduce, avoid or correct for detected fouling.

Heat exchanger performance monitoring and analysis method and system

A method for diagnosing and classifying faults in a system is provided. The method comprises acquiring operational data for at least one of a system, one or more subsystems of the system or one or more components of the one or more subsystems. Then, the method comprises analyzing the operational data using one or more diagnostic models. Each diagnostic model uses the operational data to determine a probability of fault associated with at least one of the one or more components or the one or more subsystems. Finally, the method comprises deriving an overall probability of fault for at least one of the system, the one or more subsystems, or the one or more components using the one or more probabilities of fault determined by the one or more diagnostic models and one or more hierarchical relationships between the subsystems and components of the system.

Method and system for hierarchical fault classification and diagnosis in large systems

A technique is provided for selecting among a plurality of service models for addressing serviceable events and faults in a complex machine system. Indicators established for each of the models serve as the basis for comparison to input data acquired from the complex system or from manual or semi-automated data acquisition methods. Based upon the comparisons, and upon flexible selection criteria, one or more of the service models is selected to most efficiently address the most likely root cause of the serviceable event or fault.

Complex system diagnostic service model selection method and apparatus

A technique is provided for designing and evaluating service models for components, functions, subsystems and field replaceable units in a complex machine system. At a component or item level, each model identifies various items, failure modes, and so forth which may be the root cause of anticipated serviceable events or faults. The design tools permit numerous interfaces to be used in the design of service models, and in the evaluation of the degree to which the models address detectability and isolation capabilities for the root causes of serviceable events and faults.

Complex system serviceability design evaluation method and apparatus

There is provided a central site system for communicating with at least one remote site equipment monitor, the at least one remote site equipment monitor collecting operational data concerning remote site equipment. The central site system includes a data transfer system adapted for receiving the operational data from the at least one remote site equipment monitor. The central site system also includes an operational data access system which receives the operational data from the data transfer system and stores the operational data in a data storage unit of the operational data access system. The central site system also includes a notification distribution system which receives data based on the operational data and distributes the data based on the operational data to a destination according to a predefined schedule.

Central site architecture for remote service delivery

A method for predicting a time to failure of a component in a system is presented. The method comprises obtaining a set of data measurements related to the component. The set of data measurements are representative of a plurality of parameters including a plurality of leading parameters. The method comprises generating a prediction model based upon the leading parameters considered in combination. The prediction model is then used to predict the time to failure of the component based on a set of real-time measurements, wherein the plurality of parameters are processed to predict the time to failure for the component. Finally, a confidence level for the predicted time to failure is determined based upon the plurality of parameters.

System and method for predicting component failures in large systems

Optimizing storage and retrieval of monitoring data. In one aspect of this disclosure, there is a system, method and computer readable medium that stores instructions for instructing a computer system, to optimize storage and retrieval of data. In this embodiment, a transfer manager component acquires the data from an archive and assigns predetermined storage values to specified parameters that form the data structure of the acquired data. A database stores the data acquired by the transfer manager component in accordance with the predetermined storage values. A middle tier component extracts the data in the database and interpolates the data in accordance with the predetermined storage values.

Optimizing storage and retrieval of monitoring data

Growing community of inventors

Schenectady, NY, United States of America

Mark David Osborn