Acceleration signal based approach is a main approach used to measure the displacement of polish rod in the oilfield pumping wells. In this study a learning based real time noise immunization and trend term elimination approach is proposed. During the learning acceleration signal within a period of time are firstly acquired then corresponding ARIMA model and its parameters are derived finally the period of the acceleration signal is computed by using FFT transformation and Rife Jane frequency estimation. The proposed approach bases the model obtained parameters uses Kalman filtering techniques to remove random noise computes the polish rod displacement by a quadratic integration of the period and eliminates the trend term by windowed recursive least squares method. Eventually an experiment over a pumping unit hardware in the loop plant is carried out which indicates that the proposed approach can effectively eliminate noise and trend term and obviously improve the measuring pre

acceleration signal.pdf

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