Abstract: This disclosure relates to systems and methods for performing an autonomous procedure for monitoring and diagnostics of a machine using electrical signature analysis. In one embodiment of the disclosure, a method includes providing electrical data of an electrical rotating machine associated with at least one fault frequency. While in a learning mode, the method includes converting the electrical data from a time domain to a frequency domain to obtain baseline data. While in an operational mode, the method includes converting the electrical data from the time domain to the frequency domain to obtain monitoring data. The method further includes determining, based at least on the monitoring data, a ratio value at the fault frequency, determining a rate of change of the ratio value at the fault frequency, and, optionally, issuing, based on the rate of change, an alarm concerning at least one event of the electrical rotating machine.

Abstract: Embodiments of the disclosure relate to systems and methods for monitoring and diagnosing transformer health. In one embodiment, a system incorporating a diagnostic apparatus for monitoring a power transformer can be provided. Various electrical current sensing elements and a dissolved gas analysis (DGA) apparatus are coupled to the transformer and to the diagnostic apparatus. The diagnostic apparatus can be configured to detect a through-fault in the transformer by executing an electrical current flow analysis based at least in part on electrical current values received from the electrical current sensing elements. The electrical current flow analysis involves comparing a ratio of a differential electrical current value and a restraining electrical current value to a threshold value. The diagnostic apparatus can also use DGA data provided by the DGA apparatus to detect an abnormal gas-related condition in the transformer.

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.

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.

Abstract: One or more embodiments of the disclosure pertain to a protection and diagnostic system that can generate a trip/alarm signal by executing a diagnostic procedure upon a machine that includes a rotating part. The diagnostic procedure can include using sensors to obtain performance parameters of various tagged critical and/or less critical sub-systems of the machine when the rotating part is rotating; determining, in real time, a system performance index of the machine based on the performance parameters; using a protection model to determine a sub-system performance index associated with at least one tagged sub-system of the machine; determining an asset health index based on combining the system performance index and the sub-system performance index; and generating the trip/alarm signal when the asset health index exceeds a threshold value. The protection system can include a protection device configured to receive the trip signal and execute a protective action upon the machine.

Abstract: This disclosure relates to systems and methods for performing an autonomous procedure for monitoring and diagnostics of a machine using electrical signature analysis. In one embodiment of the disclosure, a method includes providing electrical data of an electrical rotating machine associated with at least one fault frequency. While in a learning mode, the method includes converting the electrical data from a time domain to a frequency domain to obtain baseline data. While in an operational mode, the method includes converting the electrical data from the time domain to the frequency domain to obtain monitoring data. The method further includes determining, based at least on the monitoring data, a ratio value at the fault frequency, determining a rate of change of the ratio value at the fault frequency, and, optionally, issuing, based on the rate of change, an alarm concerning at least one event of the electrical rotating machine.

Abstract: One or more embodiments of the disclosure pertain to a protection and diagnostic system that can generate a trip/alarm signal by executing a diagnostic procedure upon a machine that includes a rotating part. The diagnostic procedure can include using sensors to obtain performance parameters of various tagged critical and/or less critical sub-systems of the machine when the rotating part is rotating; determining, in real time, a system performance index of the machine based on the performance parameters; using a protection model to determine a sub-system performance index associated with at least one tagged sub-system of the machine; determining an asset health index based on combining the system performance index and the sub-system performance index; and generating the trip/alarm signal when the asset health index exceeds a threshold value. The protection system can include a protection device configured to receive the trip signal and execute a protective action upon the machine.

Abstract: Embodiments of the disclosure relate to systems and methods for monitoring and diagnosing transformer health. In one embodiment, a system incorporating a diagnostic apparatus for monitoring a power transformer can be provided. Various electrical current sensing elements and a dissolved gas analysis (DGA) apparatus are coupled to the transformer and to the diagnostic apparatus. The diagnostic apparatus can be configured to detect a through-fault in the transformer by executing an electrical current flow analysis based at least in part on electrical current values received from the electrical current sensing elements. The electrical current flow analysis involves comparing a ratio of a differential electrical current value and a restraining electrical current value to a threshold value. The diagnostic apparatus can also use DGA data provided by the DGA apparatus to detect an abnormal gas-related condition in the transformer.

Abstract: Embodiments of the present disclosure relate to an integrated transformer health monitoring architecture and associated processes. In one embodiment, a method can provide: receiving protection data of a transformer from the at least one protection relay device; receiving health monitoring data of the transformer from the at least one monitoring and diagnostics (M&D) device; analyzing the received protection data and the received health monitoring data using a common time reference; monitoring, diagnosing, analyzing, or predicting a failure of the transformer based at least in part on analysis of the received protection data and the received health monitoring data; and generating an instruction to modify operation of the transformer in response to monitoring, diagnosing, analyzing, or predicting a failure of the transformer.