Mechanism of stall and surge in a centrifugal compressor with a variable vaned diffuser

To expand the stable operating range of compressors, understanding the mechanism of flow instability at low flow rates is necessary. In this paper, the mechanism of stall and surge in a centrifugal compressor with a variable vaned diffuser is experimentally investigated, where the diffuser blade setting angle can be adjusted. Many dynamic pressure transducers are mounted on the casing surface of the compressor. From the design condition to surge, dynamic pressure data is recorded throughout the gradual process. According to the signal developing status, the typical modes of compressor instability are defined in detail, such as stall, mild surge, and deep surge. A relatively high-frequency stall wave originates in the impeller and propagates to the diffuser, and finally stimulates a deep surge in the compressor. The compressor behavior during surge differs at different diffuser vane angles. When the diffuser vane angle is adjusted, both the unstable form and the core factor affecting the overall machine stability change. A specific indicator is proposed to measure the instability of each component in a compressor, which can be used to determine the best region for stability extension technologies, such as a holed casing treatment, in different compressor applications.     

离心叶轮和扩压器相互作用

采用定常和非定常数值模拟技术,研究了某跨声离心压气机级内的复杂流动,分析了叶轮与径向扩压器之间的非定常相互作用.结果表明,扩压器的势干扰使叶轮出口静压发生周期性地变化,引起叶轮后部负荷、叶尖泄漏和损失等也产生周期性地变化,影响范围达30%流向弦长.叶轮出口流场的周向不均匀性及非定常性使扩压器进口参数发生周期性的变化,导致扩压器负荷、总压恢复系数分布呈现出较强的非定常性,影响范围贯穿整个扩压器通道.      

压气机端壁自适应流通延迟失速的数值分析

端壁自适应流通方式是轴流压气机主动控制失速方法的有效措施之一,即在机匣上结合喷气与引气的方式来延迟压气机的失速,其特点是自适应流通的喷气或吹气量将随压气机的工况自我调整。采用数值模拟方法研究了端壁自适应流通方式对某轴流压气机气动性能的影响,数值计算结果表明,端壁自适应流通方式能有效地延迟失速并略微提高压气机的效率,通过详细地分析端壁自适应流通方式对压气机顶部区域流场结构的影响,揭示了其改善压气机性能的机理。     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.