A fuzzy diagnosis approach using dynamic fault trees

By incorporating digraph models, fault trees and fuzzy inference mechanisms in a unified framework, a novel approach for fault diagnosis is developed in this work. To relieve the on-line computation load, the fault origins considered in diagnosis are limited to the basic events in the cut sets of a given fault tree. The symptom occurrence order associated with each root cause is derived from system digraph with the qualitative simulation techniques. The implied candidate patterns are enumerated according to two proposed theorems and then encoded in the inference system with IF-THEN rules. The simulation results show that the proposed approach is not only feasible but also capable of identifying the most likely cause(s) of a hazardous event at the earliest possible time.     

地面驱动螺杆泵井测试仪的研制与应用

螺杆泵采油设备在油田的应用逐渐增多,但是其稳定性、可靠性和配套工艺技术的完善程度与其他常规机械采油方式相比还存在一定差距,需要寻找一种方便可行的判断泵况的方法。开发研制了螺杆泵综合测试仪,它以MCS51系列单片机为核心,通过单片机的串行通讯口控制接收和采集信号,利用有线与无线相结合的传输方式测试光杆扭矩、轴向力、转速、三相电流、三相电压和井口油压等参数,可同步或单独测量,具有精度高、灵敏度高、抗干扰性强等特点。通过300余井次现场试验,测试成功率95%以上,测试数据准确、可靠,为螺杆泵井工况诊断、优化设计提供了可靠依据。     

机电一体化技术在综合采煤设备中的应用与发展

介绍了机电一体化技术在国内外煤矿井下综采设备中的应用，并论述了机电一体化技术发展与相关技术的研究。     

肝脏占位的B超与MRI图像诊断分析

肝癌、肝血管瘤、肝囊肿是肝内常见占位性病变．笔者在临床工作中发现B超与MRI联合应用。其互补作用可提高肝脏占位的诊断率。本文通过对筛选出来的84例经B超与MRI诊断的肝脏占位病变进行分析。     

战役战术导弹目标价值排序的模糊综合评判法

针对现代战争中战役战术导弹运用的特点，确定了战役战术导弹所打击目标价值的评判指标体系，并从分析目标价值的角度出发，用模糊综合评判法对战役战术导弹所打击目标进行价值分析，建立了打击先后顺序的评判模型．最后，用实例证明了，评判模型对战役战术导弹所打击目标进行价值排序的实用性和可行性。     

基于故障树与灰关联分析的鱼雷故障诊断

将灰色关联度与故障树联合运用于鱼雷故障诊断,为鱼雷的故障诊断提供了一种新途径。在鱼雷动力系统故障树诊断模式识别中,运用灰色系统理论中的灰关联分析,通过进行关联度计算及排序,对各种故障模式发生的可能性大小作出了判断,从而为处理故障的轻重缓急、控制故障的发生以及改进系统的可靠性提供了理论依据。实例诊断表明,这种方法是有效可行的,并且诊断结果可靠。     

基于B点磁探针膛内电枢电弧长度与速度分布测量的计算机控制系统的研究

基于B点磁探针的测量原理，建立了电磁轨道炮膛内三维等离子体电枢电弧长度和电弧运动速度测量的数学模型，通过对该模型的分析给出了用于测量膛内电枢电弧长度和运动速度分布的相应推论。开发了用于测量膛内等离子体电枢电弧长度和速度的多通道计算机控制诊断系统，并进行了相应的试验研究。     

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求文针对我国天然气凝液如何利用问题,结合新技术进展,进行了初步探讨,认为原料较多的场合,应以催化脱氢或芳构化作为当前的主要加工方向。对原料较少的场合,也提出一些看法。     

Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .