Fault diagnosis method and system based on machine learning

The invention provides a fault diagnosis method and system based on machine learning, and belongs to the technical field of mechanical equipment fault diagnos.The method comprises the steps that fault sample data are obtained and preprocessed; using the preprocessed fault sample data and an XGBoost algorithm to construct a fault diagnosis model; and acquiring real-time equipment operation data, analyzing the real-time equipment operation data by using the fault diagnosis model, and outputting an equipment fault diagnosis result. According to the invention, the potential safety hazard of the equipment is effectively reduced, and compared with a traditional equipment fault diagnosis method, the method has the advantages of automation, intelligence and high diagnosis precision. 本发明提供了一种基于机器学习的故障诊断方法及系统，属于机械设备故障诊断技术领域，该方法包括：获取故障样本数据，并对故障样本数据进行预处理；利用经预处理后的故障样本数据，利用XGBoost算法构建故障诊断模型；获取实时设备运行数据，并利用故障诊断模型对实时设备运行数据进行分析，输出设备故障诊断结果。本发明有效地降低了设备的安全隐患，相对于传统的设备故障诊断方法，本发明具有自动化，智能化且诊断精度高的优点。