Shipboard machinery diagnostics and prognostics/condition based maintenance: a progress report
George D. Hadden, Peter Bergstrom, George Vachtsevanos, Bonnie Holte Bennett, Joe Van Dyke
Abstract
George D. Hadden, Peter Bergstrom, George Vachtsevanos, Bonnie Holte Bennett, Joe Van Dyke
Abstract
Developed a distributed shipboard system to perform diagnostics and prognostics on mechanical equipment (e.g. engines, generators, and chilled water systems) for the Office of Naval Research (ONR). This Condition Based Maintenance (CBM) system (called MPROS for Machinery Prognostics/Diagnostics System) consists of MEMS and conventional sensors on the machinery, local intelligent signal processing devices (called "Data Concentrators"), and a centrally located subsystem (called the PDME for Prognostics, Diagnostics, Monitoring Engine) which is designed so that it can run under shipboard monitoring systems such as ICAS (Integrated Condition Assessment System). MPROS includes and augments periodic vibration analysis by collecting data continuously from vibration and other sensors, including temperature, pressure, current, voltage, and so on. These data streams are integrated as necessary in the Data Concentrators (data fusion). A second level of integration (knowledge fusion) occurs in the PDME. At this level, the conclusions of different diagnostic and prognostic reasoning mechanisms are fused to yield the best possible analysis. In this paper, we discuss recent progress in design and implementation of the software and hardware required to support our system.
OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Developed a distributed shipboard system to perform diagnostics and prognostics on mechanical equipment (e.g. engines, generators, and chilled water systems) for the Office of Naval Research (ONR). This Condition Based Maintenance (CBM) system (called MPROS for Machinery Prognostics/Diagnostics System) consists of MEMS and conventional sensors on the machinery, local intelligent signal processing devices (called "Data Concentrators"), and a centrally located subsystem (called the PDME for Prognostics, Diagnostics, Monitoring Engine) which is designed so that it can run under shipboard monitoring systems such as ICAS (Integrated Condition Assessment System). MPROS includes and augments periodic vibration analysis by collecting data continuously from vibration and other sensors, including temperature, pressure, current, voltage, and so on. These data streams are integrated as necessary in the Data Concentrators (data fusion). A second level of integration (knowledge fusion) occurs in the PDME. At this level, the conclusions of different diagnostic and prognostic reasoning mechanisms are fused to yield the best possible analysis. In this paper, we discuss recent progress in design and implementation of the software and hardware required to support our system.
Key concepts: Prognostics, Condition monitoring, Sensor fusion, Engineering, Reliability engineering, Data acquisition, Maintenance engineering, Systems engineering