Abstract: A system for fault prediction in electrical systems. It includes a network of recording nodes that transmit data to multi-channel recorder. The nodes monitor power quality based on a number of system parameters. These data are assembled into data blocks and are analyzed to determine load factors for the system over time. Data blocks are collected over 22 cycle periods and are evaluated against a derived standard deviation factor for the given system. The standard deviation is used to determine alert and alarm levels. The constant monitoring allows the system to alert workers of a potential upcoming fault in one or more system components. In this way repairs can be made before the component fails and the system experiences a fault condition.

Abstract: A system for fault prediction in electrical systems. It includes a network of recording nodes that transmit data to multi-channel recorder. The nodes monitor power quality based on a number of system parameters. These data are assembled into data blocks and are analyzed to determine load factors for the system over time. Data blocks are collected over 22 cycle periods and are evaluated against a derived standard deviation factor for the given system. The standard deviation is used to determine alert and alarm levels. The constant monitoring allows the system to alert workers of a potential upcoming fault in one or more system components. In this way repairs can be made before the component fails and the system experiences a fault condition.

Abstract: A method for fault prediction in electrical systems. It includes a network of recording nodes that transmit data to multi-channel recorder. The nodes monitor power quality based on a number of system parameters. These data are assembled into data blocks and are analyzed to determine load factors for the system over time. Data blocks are collected over 22 cycle periods and are evaluated against a derived standard deviation factor for the given system. The standard deviation is used to determine alert and alarm levels. The constant monitoring allows the system to alert workers of a potential upcoming fault in one or more system components. In this way repairs can be made before the component fails and the system experiences a fault condition.

Abstract: A system for fault prediction in electrical systems. It includes a network of recording nodes that transmit data to multi-channel recorder. The nodes monitor power quality based on a number of system parameters. These data are assembled into data blocks and are analyzed to determine load factors for the system over time. Data blocks are collected over 22 cycle periods and are evaluated against a derived standard deviation factor for the given system. The standard deviation is used to determine alert and alarm levels. The constant monitoring allows the system to alert workers of a potential upcoming fault in one or more system components. In this way repairs can be made before the component fails and the system experiences a fault condition.