Method and system for diagnostics and monitoring of electric machines

Patent metadata

Field	Value
Publication number	US-10564204-B2
Application number	US-201715663697-A
Country	US
Kind code	B2
Filing date	Jul 28, 2017
Priority date	Jul 28, 2017
Publication date	Feb 18, 2020
Grant date	Feb 18, 2020

Abstract

A system for use with an electric machine is provided. The system includes a processor and a memory comprising a set of memory modules, which, when executed by the processor, cause the processor to perform certain operations. The operations include receiving operational data from the electric machine, and generating, based on the operational data, a first set of diagnostic data, by executing a first memory module from the set of memory modules. The operations further include generating, based on the operational data, a second set of diagnostic data, by executing a second memory module from the set of memory modules, the second memory module including a set of parameters associated with a diagnostics model of the electric machine. Furthermore, the operations include effecting, based on the operational data, the first set of diagnostic data, and the second set of diagnostic data, a change in at least one parameter.

First claim

What is claimed is:

1. A system for performing diagnostic testing on an electric machine, the system comprising:
a diagnostic unit coupled to the electric machine and configured to retrieve from the electric machine retrieve or to instruct the electric machine to send a set of sensor measurements to determine a state of the electric machine, and including:
a processor; and
a memory stored thereon a set of memory modules, which when executed by the processor, cause the processor to perform operations including:
receiving the set of sensor measurements being operational data, from the electric machine,
generating, based on the operational data, a first set of diagnostic data, by executing a first memory module being a non-adaptive module from the set of memory modules,
generating, based on the operational data, a second set of diagnostic data, by executing a second memory module being an adaptive module from the set of memory modules, the second memory module including an adaptive routine including a set of parameters associated with a diagnostics model of the electric machine, and
effecting, based on the operational data, the first set of diagnostic data, and the second set of diagnostic data, in parallel, a change in at least one parameter from the set of parameters, wherein an existence of a fault is determined using both the first set of diagnostic data and the second set of diagnostic data.

2. The system of claim 1 , wherein the sensor measurements include at least one of voltage, current, temperature, vibration signature, and insulation integrity of the electric machine.

3. The system of claim 1 , wherein the effecting is further based on data received by the processor from a remote terminal, the data received from the remote terminal being associated with an assessment from an operator.

4. The system of claim 1 , wherein non-adaptive processing performed by the non-adaptive module is based on a physics-based model of the electric machine.

5. The system of claim 1 , wherein non-adaptive processing performed by the non-adaptive module is based on a finite-element-analysis (FEA)-based model of the electric machine.

6. The system of claim 1 wherein non-adaptive processing performed by the non-adaptive module is based on a non-learning-based model of the electric machine.

7. A method for performing diagnostic testing on an electric machine, the method comprising:
coupling a diagnostic unit to the electric machine and receiving from the electric machine or instructing the electric machine, by the diagnostic unit, to send a set of sensor measurements being operational data to determine a state of the electric machine;
generating a first set of diagnostic data by the diagnostic unit, by execution of a first memory module being a non-adaptive module of the diagnostic unit and based on the operational data;
generating a second set of diagnostic data by the diagnostic unit, by execution of a second memory module being an adaptive module of the diagnostic unit and including an adaptive routine including a set of parameters associated with a diagnostic module of the electric machine and based on the operational data; and
effecting, based on the operational data, the first set of diagnostic data, and the second set of diagnostic data, in parallel, a change in at least one parameter of a diagnostic model of the diagnostic unit used to generate the second set of diagnostic data wherein an existence of a fault is determined using both the first set of diagnostic data and the second set of diagnostic data.

8. The method of claim 7 , wherein the sensor data measurements include at least one of voltage, current, temperature, vibration signature, and insulation integrity of the electric machine.

9. The method of claim 7 , wherein the effecting is further based on data received by the diagnostic unit from a remote terminal, the data received from the remote terminal being associated with an assessment from an operator.

10. The method of claim 7 , wherein non-adaptive processing performed by the non-adaptive module is based on a physics-based model of the electric machine.

11. The method of claim 7 , wherein non-adaptive processing performed by the non-adaptive module is based on a finite element analysis (FEA)-based model of the electric machine.

Assignees

• Gen Electric

Inventors

• Solomon Luke Anthony
• Gray Stuart
• Doucette Michael Richard
• Dominguez Sergio
• Sieman Alexander Richard

Classifications

• G05B23/0213

  Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols · CPC title

• G05B23/0297

  Reconfiguration of monitoring system, e.g. use of virtual sensors; change monitoring method as a response to monitoring results · CPC title

• G06F1/28

  Supervision thereof, e.g. detecting power-supply failure by out of limits supervision · CPC title

• G05B23/024

  Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks · CPC title

• G05B23/0254

  based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks · CPC title