掘进机对开挖软岩到中等强度的岩层具有独特的能力和灵活性,因此广泛应用于地下采矿和隧道作业中,对设备的生产能力准确预测是掘进机成功应用的关键问题之一。从试验法、经验法和人工神经网络方法 3个方面,介绍现有的掘进机性能预测模型及其建立背景。通过掘进机瞬时生产率的主要影响因素和统计数据,可进一步完善性能预测模型,并为设备选型和成本估算提供一定的依据。 Therefore, it is widely used in underground mining and tunneling. Accurate prediction of the production capacity of the equipment is one of the key problems in the successful application of roadheading machine. From three aspects of experiment method, experience method and artificial neural network method, the existing boring machine performance prediction model and its establishment background are introduced. Through the main influencing factors and statistical data of instantaneous productivity of roadheader, the performance prediction model can be further improved, and provide some basis for equipment selection and cost estimation.