Abstract: Systems, methods, and computer-readable media are disclosed for monitoring and diagnosing power system assets. An example method may include triggering, by a gateway device and at a first time, a capture of a first waveform from a first intelligent electronic device (IED) associated with a first asset in a power system. The method may also include transmitting, by the gateway device, the capture of the waveform to a remote device. The method may also include extracting fault features from the first waveform corresponding to different failure modes associated with the asset of the power system. The method may also include determining, based on the features extracted from first waveform, that a fault of a first fault mode has occurred in the asset. The method may also include providing an alert that the fault has been identified, wherein the alert initiates or otherwise facilitates a control action in the power system.

Abstract: Systems, methods, and computer-readable media are disclosed for monitoring and diagnosing power system assets. An example method may include triggering, by a gateway device and at a first time, a capture of a first waveform from a first intelligent electronic device (IED) associated with a first asset in a power system. The method may also include transmitting, by the gateway device, the capture of the waveform to a remote device. The method may also include extracting fault features from the first waveform corresponding to different failure modes associated with the asset of the power system. The method may also include determining, based on the features extracted from first waveform, that a fault of a first fault mode has occurred in the asset. The method may also include providing an alert that the fault has been identified, wherein the alert initiates or otherwise facilitates a control action in the power system.

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.

Abstract: Systems, methods, and computer-readable media are disclosed for monitoring and diagnosing power system assets. An example method may include triggering, by a gateway device and at a first time, a capture of a first waveform from a first intelligent electronic device (IED) associated with a first asset in a power system. The method may also include transmitting, by the gateway device, the capture of the waveform to a remote device. The method may also include extracting fault features from the first waveform corresponding to different failure modes associated with the asset of the power system. The method may also include determining, based on the features extracted from first waveform, that a fault of a first fault mode has occurred in the asset. The method may also include providing an alert that the fault has been identified, wherein the alert initiates or otherwise facilitates a control action in the power system.

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.

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.

Abstract: Provided is an electric machine health monitoring system that includes an electric machine, a data acquisition component, a local transmitter, a communications network, and a remote diagnostic unit that is configured to receive the time sequenced operational information, asset performance, and health status indicators from a local transmitter. The remote computational unit comprises software that is configured to perform diagnostic analysis of time sequenced operational information to determine the asset performance and health status of the electric machines.

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.

Abstract: Provided is an electric machine health monitoring system that includes an electric machine, a data acquisition component, a local transmitter, a communications network, and a remote diagnostic unit that is configured to receive the time sequenced operational information, asset performance, and health status indicators from a local transmitter. The remote computational unit comprises software that is configured to perform diagnostic analysis of time sequenced operational information to determine the asset performance and health status of the electric machines.

Abstract: Provided is a health monitoring system for an electric machine that includes a power converter which receives power from an electric power supply, supplies power to the electric machine, and receives operational data from the electric machine. At least one computing unit is disposed within the power converter and includes one or more software modules for performing control for the power converter and diagnostics of the electric machine.

Abstract: The disclosure provides methods and uses for alleviating and/or treating pain including pain disorders using melatonin ligands of Formula I: or pharmaceutically acceptable salts thereof wherein: n is 1 or 2; m is 0, 1 or 2; p is 0, 1, 2, 3, 4, 5, 6, 7 or 8; v is 2 or 3; A is aryl or heteroaryl; Z is 0, S or NR8; Y is chosen from hydrogen, aryl, heteroaryl, C1-C6 alkyl, C3-C6 cycloalkyl, and R is chosen from hydrogen, hydroxyl, —OCF3, CF3, C1-C8 alkyl, C1-C8 alkyloxy, C1-C8 alkylthio, halogen and —Z—(CH2p-A; R1 is chosen from C1-C4 alkyl, C3-C6 cycloalkyl, CF3, hydroxy-substituted C1-C4 alkyl, hydroxy-substituted C3-C6 cycloalkyl, and NHR5, wherein R5 is H, C1-C3 alkyl or C3-C6 cycloalkyl; R2 is chosen from hydrogen, C1-C4 alkyl, C1-C4 alkyloxy, OCF3, CF3, hydroxyl, and halogen; R3 is chosen from hydrogen, C1-C4 alkyl, C1-C4 alkyloxy, OCF3, CF3, hydroxyl and halogen; R and R3 may be connected together to form an -0-(CH2)v bridge representing with the carbon atoms to which they are attached a 5- or 6-membered h