Abstract: A current transformer having a body having an upper half and a lower half hingedly connected to the upper half, a pair of ferrite cores located within one of the upper half and the lower half of the body, the pair of ferrite cores defining a gap formed between each ferrite core of the pair of ferrite cores, and a sensor located within the gap formed between each ferrite core of the pair of ferrite cores.

Abstract: A method of managing energy by use of processing logic that comprises a load processor as a cloud service is provided. The method includes receiving power load information from a data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificial intelligence for optimization control, analyzing the received power load information to disaggregate load waveform signals and identify device-based power loads by use of a neural network to perform historical device demand and performance analysis to generate device-based demand forecasting, generating demand forecasts for the building to mitigate peak demand based on analysis of a power draw signal and the generated device-based demand forecasting, and determining whether the generated demand forecast for the building is to peak in a near future, based on threshold values of at least one of generated device-based demand forecasting, power price or cost information, and user behavior analysis.

Abstract: A system and system for motor fault detection are provided. The system includes a data collection sensor electrically coupled to a motor, and a processor functioning as a Motor Current Signature analyzer (MCSA) detecting performance conditions of the motor based on a measured power draw current data captured by the sensor and providing condition information indicative of a fault in the motor based on the detected performance conditions. The method includes measuring, by a data collection sensor, power draw current data from the motor, detecting, by a processor functioning as a Motor Current Signature analyzer (MCSA), performance conditions of the motor based on the measured power draw current data, and providing condition information indicative of a fault in the motor based on the detected performance conditions to a user.

Abstract: A current transformer having a body having an upper half and a lower half hingedly connected to the upper half, a pair of ferrite cores located within one of the upper half and the lower half of the body, the pair of ferrite cores defining a gap formed between each ferrite core of the pair of ferrite cores, and a sensor located within the gap formed between each ferrite core of the pair of ferrite cores.

Abstract: A method of managing energy by use of processing logic that comprises a load processor as a cloud service is provided. The method includes receiving power load information from a data collection system located at a building and using a cloud analysis layer that employs machine-learning and artificial intelligence for optimization control, analyzing the received power load information to disaggregate load waveform signals and identify device-based power loads by use of a neural network to perform historical device demand and performance analysis to generate device-based demand forecasting, generating demand forecasts for the building to mitigate peak demand based on analysis of a power draw signal and the generated device-based demand forecasting, and determining whether the generated demand forecast for the building is to peak in a near future, based on threshold values of at least one of generated device-based demand forecasting, power price or cost information, and user behavior analysis.

Abstract: A system and system for motor fault detection are provided. The system includes a data collection sensor electrically coupled to a motor, and a processor functioning as a Motor Current Signature analyzer (MCSA) detecting performance conditions of the motor based on a measured power draw current data captured by the sensor and providing condition information indicative of a fault in the motor based on the detected performance conditions. The method includes measuring, by a data collection sensor, power draw current data from the motor, detecting, by a processor functioning as a Motor Current Signature analyzer (MCSA), performance conditions of the motor based on the measured power draw current data, and providing condition information indicative of a fault in the motor based on the detected performance conditions to a user.