摘要
风机是煤矿企业安全生产的关键设备,其安全可靠、高效经济地运行将产生巨大的安全、经济和社会效益。故障诊断技术,特别是具有自学习、自适应、自推理等仿生能力的人工智能故障诊断方法在煤矿风机故障预警、故障识别、故障排除等方面发挥着越来越重要的作用。在对煤矿风机常见故障进行分析的基础上,对常用的煤矿风机人工智能故障诊断方法进行了分析与总结,最后对其未来的发展趋势进行了探讨。
The ventilator is the key equipment for safe production of coal mine enterprises. Sate and reliable, efficient and economic operation of ventilators will bring about huge secure, economic and social benefits. Fault diagnosis technologies, especially the artificial intelligent fault diagnosis method with self-learning, adaptive and inference capabilities, play a more and more important role in the coal mine ventilator fault alarming, fault identification and troubleshooting, etc. Firstly, common faults of coal mine ventilator are analyzed. Then artificial intelligent fault diagnostic methods for coal mine ventilator are analyzed and summarized. Lastly, the future trends of artificial intelligence in fault diagnosis of coal mine ventilator are discussed.
出处
《煤矿机械》
北大核心
2013年第12期262-264,共3页
Coal Mine Machinery
关键词
煤矿风机
人工智能
故障诊断
神经网络
coal mine ventilator
artificial intelligence
fault diagnosis
artificial neural network
