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华为网盘附件:
Suspended Load Prediction on Sucker Rod Suspension Load Based on
Artificial Neural Network
ZHOU Rui Fen1,a, BAI-Lin1,b,DONG Kang Xing1,c and DAI Yu Xin1,d
1School of Mechanical Science and Engineering, Northeast Petroleum Institute, Daqing,
Heilongjiang, China
azhourf0218@163.com, bbailin06711@126.com, cdongkx@163.com, ddyx788@163.com
Keywords: Socker rod ; suspendsion load; neural networks; prediction
Abstract. Using the test data of suspendsion load on socker rod from oilfield database, a prediction
model is presented, which adapted the improved L-M neural network algorithm and explored the 6
effect factors’ relationship: the rod stroke, frequency of strokes, rod diameter, pump diameter,
submergence depth and pump setting depth. With training the model, and higher training accuracy is
acquired, which shows using this method to predict the suspendsion load is effective. |
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