General Electric Company

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Kotesh Kummamuri Rao

Gregory John Goodrich

Robert Joseph Iasillo

Minesh Ashok Shah

Bruce Gordon Norman

Atanu Talukdar

Johan Michael Reimann

Andrew J Travaly

Ajai Singh

Guruprasad Srinivasan

Michael Brynn House

Hardev Singh

Marzia Sepe

Riccardo Garbin

Gilbert Scott Reveille

Venkatesh Kattigari Madyastha

Jose Mendoza

Jose Leon Vega

James Clark Powzyk

Yan Chen

Senthilkumar Datchanamoorthy

Steven Glenn Ostrander

Ravi Yoganatha Babu

Vinod Reddy

A method to monitor the health status of a rolling bearing of a machinery, including a first acquiring step of a rotation speed value of a shaft coupled to the rolling bearing, a second acquiring step of a first signal generated by a vibration sensor located on the machinery in a position distant from the rolling bearing, and a first calculating step of a variation of the shaft rotation speed value during a predetermined time interval, and if the calculated variation of the rotation speed falls within a predetermined variation interval, performing a first filtering step of the first signal with a first algorithm based on a vibration produced by parts of the machinery different from the bearing at the rotation speed value, so as to obtain a second signal representative of a bearing health status.

Method and system to monitor the health status of a rolling bearing of a machinery, and machinery equipped with said system

A controller includes a processor and memory. The memory stores instructions that, when executed, are configured to cause the processor to receive measurements pertaining to a measured operation parameter of at least a portion of a turbine system. The instructions are also configured to cause the processor to generate a customized model for the at least the portion of the turbine system. Moreover, the instructions are configured to cause the processor to estimate an estimated value using the received measurements. The estimated value pertains to a parameter of the turbine system. Furthermore, the instructions are configured to cause the processor to using the customized model, reduce or remove at least some environmental conditions from a corrected estimated value derived from the estimated value.

Model-based performance estimation

A method for triggering a partial discharge acquisition from an energy generating device is described. The method includes generating a power source sensed signal by sensing electromagnetic energy output from the energy generating device, producing an present flux density trace from the power source sensed signal, and determining a lack of variation in timing from at least one of the present flux density trace and a comparison between the present flux density trace and at least one prior flux density trace.

Systems and methods for triggering a partial discharge acquisition

A system for digitization of work processes in a power plant having a gas turbine including at least one processor system having a controller. The processor receives power plant data and the controller preferably controls the gas turbine. At least one interface device is communicatively coupled to the processor system for communicating the data received from the processor system to at least one of a mobile computing system and a computer system carried by a mobile user. The controller is capable of receiving instructions from the mobile user to control the gas turbine. The system further includes a local area network (LAN) in communication with the at least one interface device. At least one antenna assembly having a transceiver system for transmitting and receiving signals from the at least one interface device is provided. A network server system is communicatively coupled to the at least one antenna assembly via a wireless communication network, the server computer including a database for storing application data accessible by the mobile user.

Digitization of field engineering work processes at a gas turbine power plant through the use of portable computing devices operable in an on-site wireless local area network

A computer implemented process is provided for assessing and characterizing the degree of success or failure of an operational event of a machine system such as a fluid compressor machine or turbine machine or the like on a continuous numerical scale. The computer implemented process develops and tracks machine unit signatures, machine site signatures and machine fleet signatures to evaluate various operational events and provide fault detection. At least some sensor data acquired from the machine system during an operational event is transformed to correct or at least reduce variabilities in the data caused by ambient conditions and fuel quality. The transformed data is then analyzed using statistical methods to determine how closely the operational event conforms to an expected normal behavior and the information is used to develop a single comprehensive quality assessment of the event. By saving, tracking and updating operational event assessments over time, machine/component degradation may be recognized at any early stage and corrective action may be initiated in advance of a catastrophic failure.

Method for developing a unified quality assessment and providing an automated fault diagnostic tool for turbine machine systems and the like

A method for detecting a shorted turn in a synchronous machine having a rotor using a magnetic flux probe is disclose having the steps of: monitoring a signal from the flux probe during on-line operation of the machine; integrating the flux probe signal to generate a flux density data trace that repeats during each rotor revolution; upon detecting movement in the flux density zero-crossing, capturing the flux probe signal for a current rotor revolution for a variety of machine load conditions, and performing a shorted turn analysis with the captured flux signal data.

Online detection of shorted turns in a generator field winding

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Pearland, TX, United States of America

Kotesh Kummamuri Rao