Analysis of electrical signatures has been in use for some time for estimating the condition of induction motors, by extracting spectral indicators from motor current waveforms. In most applications, motors are used to drive dynamic loads, such as pumps, fans, and blowers, by means of power transmission devices, such as belts, couplers, gear-boxes. Failure of either the electric motors or the driven loads is associated with operational disruption. The large costs associated with the resulting idle equipment and personnel can often be avoided if the degradation is detected in its early stages prior to reaching failure conditions. Hence the need arises for cost-effective detection schemes not only for assessing the condition of the motor but also of the driven load. This prompts one to consider approaches that use no add-on sensors, in order to avoid any reduction in overall system reliability and increased costs. This paper presents an experimentally demonstrated sensorless approach to detecting varying levels of cavitation in centrifugal pumps. The proposed approach is sensorless in the sense that no mechanical sensors are required on either the pump or the motor driving the pump. Rather, onset of pump cavitation is detected using only the line voltages and phase currents of the electric motor driving the pump. Moreover, most industrial motor switchgear are equipped with potential transformers and current transformers which can be used to measure the motor voltages and currents. The developed fault detection scheme is insensitive to electric power supply and mechanical load variations. Furthermore, it does not require a priori knowledge of a motor or pump model or any detailed motor or pump design parameters; a model of the system is adaptively estimated on-line. The developed detection algorithm has been tested on data collected from a centrifugal pump connected to a 3 φ, 3 hp induction motor. Several cavitation levels are staged with increased severity. In addition to these staged pump faults, extensive experiments are also conducted to test the false alarm performance of the algorithm. Results from these experiments allow us to offer the conclusion that for the cases under consideration, the proposed model-based detection scheme reveals cavitation detection times that are comparable to those obtained from vibration analysis with a detection threshold that is significantly lower than used in industrial practice.
Geometric parameters optimization of planar interdigitated electrodes for bioimpedance spectroscopy