Novel physical network algorithm for indirect measurement of polished rod load of beam-pumping unit

Abstract

A novel neural network algorithm for indirect measurement of the polished rod load of the beam-pumping unit is proposed. The dynamometer card is a two-dimension graph of polished rod load versus horse head position, and it is widely used for working state monitoring of pumping unit. The drift problem of load sensor makes the direct measurement of polished rod load not economical and practical, so indirect measurement of polished rod load is crucial. Through the analysis of the mechanical characteristics of the pumping unit, a neural network with physical meaning (physical network) is designed. The experiment shows that the physical network can simulate the energy transfer process properly with only 18 training data items, which is about 1% of other data-driven models, and maintains good performance under different down-hole conditions.

Keywords

• rods (structures)
• dynamometers
• neural nets
• mechanical engineering computing
• electric drives
• spatial variables measurement
• graph theory
• down-hole conditions
• data-driven models
• energy transfer process
• load sensor
• drift problem
• working state monitoring
• horse head position
• two-dimension graph
• dynamometer card
• indirect polished rod load measurement
• physical meaning
• economical measurement
• novel neural network algorithm
• beam-pumping unit
• novel physical network algorithm