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To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery using the negative selection mechanism of biology immune system. This method uses techniques of biology clone and learning mechanism to improve the negative selection algorithm to generate detectors possessing different monitoring radius, covers the abnormality space effectively, and avoids such problems as the low efficiency of generating detectors, etc. The result of an example applying the presented monitoring method shows that this method can solve the difficulty of obtaining fault samples preferably and extract the turbine state character effectively, it also can detect abnormality by causing various fault of the turbine and obtain the degree of abnormality accurately. The exact monitoring precision of abnormality indicates that this method is feasible and has better on-line quality, accuracy and robustness. 相似文献
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In order to investigate the flow-induced vibration in the shroud passage of centrifugal pump and predict rotordynamic forces of centrifugal pump rotor system,an analysis of rotordynamic forces arising from shrouded centrifugal pump is presented. CFD techniques were utilized to analyze the full three-dimensional viscous,primary/secondary flow field in a centrifugal pump impeller to determine rotordynamic forces. Multiple quasi-steady solutions of an eccentric three-dimensional model at different whirl frequency ratios yielded the rotordynamic forces. The skew-symmetric stiffness,damping,and mass matrices were obtained by second-order least-squares analysis. Simulation of the coupled primary/secondary flow field was conducted,and the complex flow characteristics in the flow field of a shroud passage were achieved including the mean velocity and pressure,as well as the eddy in a large scale of flow field due to viscosity. The rotordynamic force coefficients were calculated,and the results were in good agreement with those of experiment except for the direct inertial coefficient without the consideration of whirling forces from the impeller primary flow passage. 相似文献
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Extension matrix(EM)and ID3 are two main algorithms with wide applicationin the field of machine learning,but analysis shows EM may Cause false diagnosis and ID3may cause fail diagnosis.This paper presents a new combination of these two methods toachieve a new method called entropy extension matrix(EEM)and a new concept ofgeneralization association ability(GAA).Results show that this algorithm has propertiesbetter than those of EM and ID3. 相似文献
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涡轮转子在快速起动的过程中会产生较大的热应力,影响转子的热疲劳寿命。结合遗传算法与转子结构热分析,提出发动机起动温升控制曲线非单调参数化,对涡轮转子快速起动过程中的温升控制曲线进行优化设计。优化过程以转子最大热应力为目标函数,计算搜索最优解,并研究温升控制曲线对转子最大热应力的影响。结果显示,优化后的发动机快速起动温升控制曲线可以有效地降低转子的最大热应力和缩短快速起动时间。同时,为了验证提出的涡轮转子快速起动温升曲线优化设计方法的有效性,搭建转子热冲击应力测试试验台,通过对比优化前后温升曲线下的转子最大热应力,验证了理论分析结果。提出的优化设计方法可以为发动机设计初期的快速起动控制方案设计提供一定借鉴。 相似文献
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声发射信号到达时间的信息,对于声发射事件的定位、识别以及声发射源机理分析都是非常重要的。实际应用中,常用人工读取或通过设定幅值阈值来获取信号的到达时间。针对以上常用方法的缺点,结合噪声信号的AR模型和声发射信号的AR模型,应用Akaike信息准则,实现了对声发射信号到达时间的自动识别。对实验数据的识别结果显示,该方法对信号的幅频特性变化比较敏感。在相同信噪比的情况下,该方法识别的偏差要小于阈值法。当信噪比较低时,阈值法可能会给出错误的结果,而该方法仍然能够给出较准确的结果。 相似文献
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