General Electric Company

Ravi Yoganatha Babu

Achalesh Kumar Pandey

Vinay Bhaskar Jammu

Bhasker Rao Keely

Vinod Kumar

Nilesh Tralshawala

Chayan Mitra

Aninda Bhattacharya

Kunal Ravindra Goray

Sheri George

Nishith Pramod Vora

Richard John Rucigay

Munish Vishwas Inamdar

Rama Venkata Mahajanam

Vivek Venugopal Badami

Thomas James Batzinger

Jacob John Kittleson

Scott Mordin Hoyte

Soumen De

Necip Doganaksoy

Sudhanshu Rai

Mandar Diwakar Godbole

Wangming Lu

Prashanth D'Souza

Slawomir Marian Zaremba

Viany Bhaskar Jammu

This disclosure provides systems and methods for using a health monitoring system with acoustic emissions (AE) signals and the resonance frequency of the damage state of a component in a machine to monitor component health. AE signals collected from sensors on an operating machine are analyzed to identify signal features or events that correspond to component resonance frequencies. The AE signal features proximate to the component resonance frequencies and how those features and the component resonance frequency changes over time enable the identification and monitoring of damage states, such as cracks in the stator vanes of a compressor, gas turbine, steam turbine, or generator.

System and method for monitoring component health using resonance

A system is disclosed. The system includes a processing subsystem that receives component data signals corresponding to a plurality of parameters of a device, wherein the processing subsystem generates one or more sets of state category component data by allocating the component data signals into respective one or more sets of state category component data, determines a plurality of first dynamic thresholds and a plurality of second dynamic thresholds corresponding to at least one of the one or more sets of state category component data based upon a respective set of state category component data in the one or more sets of state category component data and a respective parameter in the plurality of parameters, and determines an impending trip of the device utilizing the plurality of first dynamic thresholds and the plurality of second dynamic thresholds.

Systems and methods for prediction of trips

A monitoring system for use with a turbine engine is described herein. The turbine engine includes a compressor and at least one compressor bleed valve coupled to the compressor. The monitoring system includes at least one sensor that is for sensing an operational parameter of the compressor bleed valve, and a controller that is coupled to the sensor and the compressor bleed valve. The controller is configured to determine an operating mode of the turbine engine and receive a monitoring signal indicative of the sensed operational parameter. The controller is also configured to calculate at least one operational value of the compressor bleed valve based at least in part on the sensed operational parameter. The controller is further configured to determine a condition of the turbine engine based at least in part on the calculated compressor bleed valve operational value.

System and method of monitoring turbine engines

A system including a plurality of sensing devices configured to generate acoustic emission (AE) signals that are representative of acoustic emission waves propagating through a plurality of stator vanes is presented. The system further includes a processing subsystem that is in an operational communication with the plurality of sensing devices, and the processing subsystem is configured to generate a dynamic threshold based upon an initial threshold and the AE signals, determine whether a plurality of signals of interest exist in the AE signals based upon the dynamic threshold, extract the plurality of signals of interest from the AE signals based upon the dynamic threshold, determine one or more features corresponding to the plurality of signals of interest, and analyze the one or more features to monitor and validate the health of the plurality of stator vanes.

System and method for monitoring health of stator vanes

Embodiments of the invention include an inspection system to inspect internal components of a compressor of a gas turbine engine. The inspection system includes an image recording assembly having one or more image recording devices, light sources, storage devices, and power supplies. The image recording assembly may be inserted into a compressor without removal of the compressor housing or disassembly of the compressor. The image recording assembly may be removably coupled to a rotary component of the compressor, e.g., a rotor blade, and used to record images of stationary components, e.g., stator vanes, of the compressor. The images may be inspected to identify wear and/or defects in the stationary components, e.g., stator vanes.

System and method for inspection of stator vanes

A system is disclosed that includes an image recording assembly for recording images of a stator vane of a compressor and a mechanism configured to magnetically couple the image recording assembly to a rotor blade of a compressor. Additional systems are provided that include image recording assemblies. Methods implementing the disclosed systems are also provided.

Image recording assemblies and coupling mechanisms for stator vane inspection

A system for use in monitoring operation of a rotor assembly is provided. The system includes a plurality of clearance sensors including at least a first clearance sensor configured to measure a distance between the first sensor and a surface of a lockwire tab, and a monitoring unit coupled to the plurality of clearance sensors, the monitoring unit configured to receive measurements from the plurality of clearance sensors, and determine whether a crack exists in the rotor assembly based on the received measurements.

Systems and methods for use in monitoring operation of a rotating component

A method for monitoring the health of a compressor of a gas turbine is disclosed. The method includes receiving a plurality of turbine data points, wherein the plurality of turbine data points may include one or more operating parameters, at least one of a computer discharge temperature (CTD), and one or more performance parameters. The plurality of turbine data points may be categorized based on the one or more operating parameters. A statistical variability measure of at least one of the CTD and the one or more performance parameters may be computed for each of the plurality of bands. An alarm indicator may be computed based on the at least one statistical variability measure. The method may also include combining two or more of the operating parameters, the CTD and the performance parameters using sensor fusion techniques. The alarm indicator may be computed based on the combined parameters.

Method and system for compressor health monitoring

Systems and methods for prediction of gas turbine trips due to component failures such as electro-hydraulic valve (gas control valve) system failures. Exemplary embodiments include prediction of gas turbine trips due to component failures, the method including collecting raw gas turbine operational data and using the raw gas turbine operational data to generate a prognostic indicator for the prediction of a turbine trip due to the failed gas control valves.

System and method for prediction of gas turbine trips due to gas control valve failures

A method is provided for the monitoring of heat transfer devices. The method includes the acts of receiving data from a heat transfer device, and computing a performance indicator indicative of an incipient anomaly condition of the heat transfer device based upon the received data, and/or computing a normalized efficiency of the heat transfer device. The normalized efficiency represents a corrected efficiency that isolates effects of a process parameter on performance of the heat transfer device. The data represents a measurable process parameter or a change in a measurable process parameter in the heat transfer device. The method receives the data and computes a performance indicator to predict performance degradation of the heat transfer device over time based upon the received data.

Method for monitoring performance of a heat transfer device

Systems and methods for prediction of gas turbine trips due to component failures such as thermocouple failures. Exemplary embodiments include prediction of gas turbine trips due to component failures, including collecting raw gas turbine operational data and using the raw gas turbine operational data to generate a prognostic indicator for the prediction of a turbine trip due to the failed thermocouples.

System and method for prediction of gas turbine trips due to thermocouple failures

A system for isolating effects of one or more process parameters on performance of a heat transfer device is provided. The system includes an efficiency correction unit that is adapted to receive data from the heat transfer device. The data is representative of one or more measurable process parameters or a change in the one or more measurable process parameters of the heat transfer device. The efficiency correction unit is also configured to compute a normalized efficiency of the heat transfer device. The normalized efficiency represents a corrected efficiency that isolates effects of one or more process parameters on performance of the heat transfer device.

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Bengaluru, India

Ravi Yoganatha Babu