Performance Prediction Method of Centrifugal Pump Based on Improved QP Model

doi:10.3901/JME.2023.13.280

Abstract

Abstract: Centrifugal pumps are widely used in various fields of industrial production, and they account for 22% of the industrial electricity consumption. A new sensorless online monitoring technology is proposed to achieve effective monitoring of energy consumption of centrifugal pump units by replacing the sensor monitoring methods due to high cost and high failure rate. On the basis of a standard flow rate Q and shaft power P (QP) prediction model, a multistage centrifugal pump driven by an asynchronous motor is tested in lab to obtain performance data under different operating conditions. The centrifugal pump characteristic curves at the different speeds are modified to regular speeds by using the affinity law. A predictive mathematical model of flow rate versus power and speed, and head versus flow rate and speed is developed. An improved QP model with speed difference weighting algorithm is proposed based on the results of flow and head error analysis at different speeds, and carried out error analysis on the flow rate and head estimation models with four typical weighting functions. Results showed that the improved QP model with weight function III has the smallest average prediction errors, its flow rate relative error is 3.66% and head relative error is 1.51%. The prediction accuracy is significantly improved compared with the standard QP model. The improved QP estimation model not only improves the prediction accuracy of centrifugal pump operation status, but also provides a theoretical basis for the development of senseless online monitoring technology of centrifugal pump.

Key words: centrifugal pump, performance estimation, sensorless measurement, QP model

CLC Number:

TG156

WU Yuezhong, ZHANG Ting, FEI Minghao, WU Denghao, REN Yun. Performance Prediction Method of Centrifugal Pump Based on Improved QP Model[J]. Journal of Mechanical Engineering, 2023, 59(13): 280-289.

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