Electrical signature analysis of electrical rotating machines
First Claim
1. A system comprising:
- an electrical rotating machine;
a data acquisition device configured to detect and provide at least electrical data associated with the electrical rotating machine; and
an equipment controller communicatively coupled to the data acquisition device, the equipment controller being configured to;
in a learning mode;
ascertain initial information associated with the electrical rotating machine;
assign a plurality of operational conditions associated with the electrical rotating machine to a plurality of buckets, wherein at least one bucket of the plurality of buckets is associated with at least one load window selected from a plurality of load windows;
record the electrical data to obtain a pre-defined number of sets of learning data;
determine, based at least on the initial information and the learning data, that the electrical rotating machine is in a healthy condition; and
based on a determination that the electrical rotating machine is in the healthy condition;
obtain, based on the learning data, baseline data associated with the at least one bucket;
generate, based on the baseline data, a threshold associated with the at least one bucket and at least one fault frequency associated with the electrical rotating machine; and
generate, based on the threshold and the baseline data, at least one alarm concerning a state of the electrical rotating machine, the electrical rotating machine running within operational conditions associated with the at least one bucket, wherein the equipment controller configured to generate the threshold is further configured to;
compute variations for the sets of the learning data associated with the at least one bucket;
select sets with variation less than a pre-determined value;
convert the learning data associated with the selected sets from a time domain to a frequency domain to obtain sets of frequency data;
average the sets of frequency data to obtain the baseline data;
compute a standard deviation of the frequency data for at least one fault frequency; and
determine, based on the standard deviation, the threshold associated with the at least one fault frequency and the at least one bucket, wherein the equipment controller configured to generate the threshold is further configured to compute the threshold by multiplying a standard deviation by a predetermined constant value, the predetermined constant value being selected based on an expected false positive error.
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Accused Products
Abstract
This disclosure relates to systems and methods for electrical signature analysis of electrical rotating machines. In one embodiment of the disclosure, a method includes ascertaining initial information associated with an electrical rotating machine, assigning a plurality of operational conditions associated with the machine to a plurality of buckets, and recording the electrical data to obtain a pre-defined number of sets of learning data. The method further includes determining, based at least on the initial information and the learning data, that the machine is in a healthy condition, obtaining, based on the learning data, baseline data associated with at the at least one bucket, and generating, based on the baseline data, a threshold associated with the bucket and at least one fault frequency associated with the machine. The method further includes generating, based on the threshold and the baseline data, alarms concerning a state of the electrical rotating machine.
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Citations
16 Claims
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1. A system comprising:
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an electrical rotating machine; a data acquisition device configured to detect and provide at least electrical data associated with the electrical rotating machine; and an equipment controller communicatively coupled to the data acquisition device, the equipment controller being configured to; in a learning mode;
ascertain initial information associated with the electrical rotating machine;assign a plurality of operational conditions associated with the electrical rotating machine to a plurality of buckets, wherein at least one bucket of the plurality of buckets is associated with at least one load window selected from a plurality of load windows; record the electrical data to obtain a pre-defined number of sets of learning data; determine, based at least on the initial information and the learning data, that the electrical rotating machine is in a healthy condition; and based on a determination that the electrical rotating machine is in the healthy condition; obtain, based on the learning data, baseline data associated with the at least one bucket; generate, based on the baseline data, a threshold associated with the at least one bucket and at least one fault frequency associated with the electrical rotating machine; and generate, based on the threshold and the baseline data, at least one alarm concerning a state of the electrical rotating machine, the electrical rotating machine running within operational conditions associated with the at least one bucket, wherein the equipment controller configured to generate the threshold is further configured to; compute variations for the sets of the learning data associated with the at least one bucket; select sets with variation less than a pre-determined value; convert the learning data associated with the selected sets from a time domain to a frequency domain to obtain sets of frequency data; average the sets of frequency data to obtain the baseline data; compute a standard deviation of the frequency data for at least one fault frequency; and determine, based on the standard deviation, the threshold associated with the at least one fault frequency and the at least one bucket, wherein the equipment controller configured to generate the threshold is further configured to compute the threshold by multiplying a standard deviation by a predetermined constant value, the predetermined constant value being selected based on an expected false positive error. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for electrical signature analysis, the method comprising:
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providing, by a data acquisition device communicatively coupled to an electrical rotating machine, at least electrical data associated with the electrical rotating machine; ascertaining, by an equipment controller communicatively coupled to the data acquisition device, initial information associated with the electrical rotating machine; assigning, by an equipment controller, a plurality of operational conditions associated with the electrical rotating machine to a plurality of buckets, wherein at least one bucket of the plurality of buckets is associated with at least one load window selected from a plurality of load windows; recording, by the equipment controller, the electrical data to obtain a pre-defined number of sets of learning data; determining, by the equipment controller, based at least on the initial information and the learning data, that the electrical rotating machine is in a healthy condition; and based on a determination that the electrical rotating machine is in the healthy condition; obtaining, by the equipment controller and based on the learning data, baseline data associated with at the at least one bucket; generating, by the equipment controller and based on the baseline data, a threshold associated with the at least one bucket and the at least one fault frequency associated with the electrical rotating machine; and generating, based on the threshold and the baseline data, an alarm concerning a state of the electrical rotating machine running within operational conditions associated with the at least one bucket, wherein generating the threshold includes; computing, by the equipment controller, variations for sets of the learning data associated with the at least one bucket; selecting, by the equipment controller, sets with variation less than a pre-determined value; converting, by the equipment controller, the learning data associated with the selected sets from a time domain to a frequency domain to obtain sets of frequency data; averaging, by the equipment controller, the sets of frequency data to obtain the baseline data; computing, by the equipment controller, a standard deviation of frequency data at the at least one fault frequency; and determining, by the equipment controller and based on the standard deviation, the threshold associated with the at least one bucket, wherein the threshold is determined by multiplying a standard deviation by a predetermined constant, the predetermined constant being selected based on an expected false positive error. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A system for electrical signature analysis, the system comprising:
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an electrical rotating machine; a data acquisition device configured to detect and provide at least electrical data associated with the electrical rotating machine, wherein the electrical data includes a current data and a voltage data; and an equipment controller communicatively coupled to the data acquisition device, the equipment controller configured to; in a learning mode; ascertain initial information associated with the electrical rotating machine; assign a plurality of operational conditions associated with the electrical rotating machine to buckets, wherein at least one bucket of the plurality of buckets is associated with at least one load window selected from a plurality of load windows; record the electrical data to obtain a pre-defined number of sets of learning data; determine, based at least on the initial information and the learning data, that the electrical rotating machine is in healthy condition; and based on the determination that the electrical rotating machine is in the healthy condition; obtain, based on the learning data, baseline data associated with at least one bucket; and generate, based on the baseline data and a predetermined constant, a threshold associated with the at least one bucket and with the at least one fault frequency associated with the electrical rotating machine, the predetermined constant being selected based on an expected false positive error; determine a noise floor based on the baseline data; and adjust the threshold based on the noise floor; in a monitoring mode; record the electrical data to obtain incoming data; determine a current bucket associated with the incoming data; determine that the baseline data and the threshold are present for the current bucket; and based on the determination that the baseline data and the threshold are present; determine that incoming data exceed the baseline data by more than the threshold at the at least one fault frequency; and based on the determination that the incoming data exceed the baseline data by more than the threshold for the at least one fault frequency, issue an alarm concerning at least one event associated with the electrical rotating machine; and if the baseline data and the threshold are not present; record the incoming data to the learning data associated with the current bucket; and switch to the learning mode.
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Specification