往复泵是广泛应用于钻井、注水和压裂等工艺中的重要设备，其工作条件十分恶劣。往复泵能否正常运转对油田安全生产十分重要，因此对其易损件，如泵阀、活塞-缸套副、柱塞-密封副等的状态监测和趋势预测，成为往复泵故障诊断的关键问题。笔者主要探讨了往复泵的故障发展趋势，针对其故障诊断与预测的难点，采用组合预测模型进行趋势预测。通过往复泵预测实例分析，对往复泵液力端进行单步和多步预测。

The reciprocating pump which is important equipment in the processes is widely used in drilling, water injection and fracturing. The working condition is severe, so the condition of monitoring and trend prediction of its wearing parts, such as pump valve, piston-cylinder liner and plunger-seal pair become the key problem to the safe operation of reciprocating pumps. This paper researches on fault trend prediction method of reciprocating pump based on gray-neural network, and evaluation of equipment condition using the prediction results. According to fault development trend and difficulties of fault diagnosis and prediction of reciprocating pumps, a combinative prediction model with grey and neural network is selected, which has higher prediction accuracy and the effective degrees of prediction.