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探讨了离心机机械故障诊断专家系统的设计及实现构思。本系统设计为基于故障树结构的智能化机械故障诊断进程，采用人工交互式人机对话方式；通过对离心机运转状况的实时振动数据采样，结合数字信号提纯及处理；建成自学习机器振动信息图形数据库和专家经验知识库；以谱分析等主要精确诊断手段，进行故障主导征兆参数识别来确定故障模式。拟通过故障体系分析，提高诊断精度和效率，实现诊断过程智能化。
The design and realization of centrifuge mechanical fault diagnosis expert system are discussed. The system is designed as an intelligent mechanical fault diagnosis process based on fault tree structure, using artificial interactive man-machine dialogue mode; through real-time vibration data sampling of centrifuge operating conditions, combined with digital signal purification and processing; built self-learning machine vibration information Graphic database and expert experience knowledge base; the main accurate diagnosis methods such as spectral analysis, fault symptom predominant symptom parameter identification to determine the failure mode. It is proposed to analyze the fault system to improve the diagnostic accuracy and efficiency and to realize the intelligent diagnosis process.