Motor parameters estimation from industrial electrical measurements

Abstract

Voltage and current sensors integrated in modern electrical equipment can enable extraction of advanced information on the network and the connected devices. While traditional methods for protection and network managements rely upon processing of these signals at low speed, high-frequency processing of the raw current and voltage signals can unveil information about the type of electrical load in the networks. In particular, the common case of three-phase induction machines is considered in this paper. Motor parameters are instrumental information for control, monitoring and diagnostic. A classical approach is to measure motor parameters using off-line dedicated measurements. In this paper, we propose a method for motor parameters estimation from electrical measurements during motor start-up. Given samples of current and voltage signals during motor start-up, the model parameters are identified using classical non-linear system identification tools. While the classical theory is developed using current sensors, in this paper the method is extended to a common type of industrial current sensors, i.e., Rogowski coil sensors, and signal processing methods are presented to overcome the non-ideality caused by this type of sensors. Numerical tests performed on real data show that effective motor parameters identification can be achieved from the raw current and voltage measurements.