提出了一种基于多传感器信息融合技术对油品质量进行在线监测的新方法, 通过对粘度、温度、介电常数的测量, 建立了神经网络油品质量状态监测模型, 并给出了系统的设计方案。

复杂、并发故障诊断的难点在于这些故障的振动信号很复杂，特征很难获取。文中阐述了从实例数据库中挖掘故障特征的整体结构，定义了信号的绝对、相对和梯度特征及相应的绝对、相对和梯度模式实例，进而阐述了应用模糊聚类分析挖掘特征模式的方法。最后以往复式压缩机实例挖掘系统为例说明了该原理的应用。

采用最新发展的多媒体信息技术、监控技术和通信技术，建立了集计算机监控、视频监控、调度和管理等于一体的计算机综合监控系统，系统包括视频、检测、网络与数据库、优化调度和生产管理与决策5个既相对独立又互有联系的子系统。在大型水利工程中实现了混凝土生产、输送、浇注过程的综合监控和管理，对生产质量和成本进行控制，对经济效益进行分析与评价等，为复杂环境下大型水利施工的生产、调度和管理提供了一套科学而有效的法。 系统已经应用于三峡工程的大坝浇注生产中，并发挥了重要作用。

The vibration behaviour of a rotor system supported by hydrodynamic bearing is significantly influenced by the dynamic characteristics of the bearings. An identification procedure for stimating bearings oil-film coefficients is developed in this work. Eight linearized oil-film coefficients are identified by fitting the measured complex functions of frequency response to those calculated theoretically. The theoretical model and reliability are examined by computer simulation. From error analysis, some interesting conclusions are reached and a new identification method is suggested in order to reduce the influence of phase measurement errors on estimated results.

A new strategy for the techniques of monitoring and diagnosing hydrodynamic bearing-rotor systems is recommended in this paper. The strategy integrates the traditional technique of spectrum and statistics analysis(backward inference) with the application of knowledge and information of rotor-bearing dynamics and tribology (forward inference).This strategy has been used to develop a monitoring and diagnosing system for rotating machinery and examples of the successfuI application of the system are given.