一种整体式天然气压缩机气阀故障诊断技术研究CSCD

整体式天然气压缩机在石油化工领域广泛应用,压缩机的正常工作对安全生产具有重要意义。为了有效诊断整体式压缩机气阀部件的故障,采用了Daubechies小波基函数对ZTY470型整体式天然气压缩机气阀振动信号的分解重构原理,详细介绍了以振动信号的能量为故障特征的故障诊断过程。对气阀阀片断裂和弹簧断裂的故障振动信号进行了小波包分析,并与正常工作时的信号进行了对比。实验表明该方法能准确的进行故障诊断和故障定位,证明了对整体式天然气压缩机气阀故障诊断的有效性。     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

基于一致性融合和神经网络的航空发动机气路系统故障诊断方法

以信息融合为基础,运用GRNN神经网络对航空发动机气路系统进行故障诊断,提出了一种基于一致性融合和神经网络相结合的故障诊断方法。试验结果表明,该方法能快速识别航空发动机气路系统故障,并且对其他机械设备的故障诊断具有一定的参考价值。     

Nonlinear dynamic modeling of a helicopter planetary gear train for carrier plate crack fault diagnosis

Planetary gear train plays a significant role in a helicopter operation and its health is of great importance for the flight safety of the helicopter. This paper investigates the effects of a planet carrier plate crack on the dynamic characteristics of a planetary gear train, and thus finds an effec-tive method to diagnose crack fault. A dynamic model is developed to analyze the torsional vibra-tion of a planetary gear train with a cracked planet carrier plate. The model takes into consideration nonlinear factors such as the time-varying meshing stiffness, gear backlash and viscous damping. Investigation of the deformation of the cracked carrier plate under static stress is performed in order to simulate the dynamic effects of the planet carrier crack on the angular displacement of car-rier posts. Validation shows good accuracy of the developed dynamic model in predicting dynamic characteristics of a planetary gear train. Fault features extracted from predictions of the model reveal the correspondence between vibration characteristic and the conditions (length and position) of a planet carrier crack clearly.     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

基于PaSR模型的低旋流燃烧大涡模拟

为了深入理解低旋流流场特征和燃烧稳定性,基于OpenFOAM平台,采用动态k方程模型和有限速率PaSR模型对甲烷/空气预混低旋流燃烧进行了大涡模拟,研究了气流入口速度、当量比和压力等流场参数对流场结构和燃烧非稳态特性的影响,分析了流场大尺度结构与火焰相互作用。结果表明,流场结构和火焰抬升高度受入口速度影响较小,流场和火焰形态能够保持自相似性;随着当量比和压力提高,流场扩张性增强并在燃烧区下游产生回流区,火焰稳定不依赖回流区,根部火焰锋面形状由U形转变为W形,火焰抬升高度降低。火焰锋面稳定在剪切层,剪切层产生的周期性有序涡结构引起当地流场速度脉动和火焰表面褶皱,反映了流场非稳态特性;通过剪切层监测点瞬时轴向速度分析,涡结构特征频率随速度增大而提高,由250Hz提高至300Hz,随当量比和压力提高而降低,由250Hz降低至125Hz。     

基于综合模糊聚类算法的液体火箭发动机故障诊断

基于液体火箭发动机正常及故障状况数据的完备程度和数据质量的不断提高,提出一种基于数据驱动的综合模糊聚类算法用于故障诊断。采用模糊c均值(FCM)算法对已知正常样本数据进行聚类得到最优的聚类中心,将所得到的聚类中心作为先验样本数据用于传递闭包法最优分类结果的选择从而得到故障检测结果,该算法只需要少量的正常先验样本数据就能快速、准确的检测出故障;随后采用FCM算法进行故障分类,可以根据现有的故障数据库进行聚类得到对应的故障类型,并且可以给出故障幅值范围。模型仿真结果表明:该算法对故障的检测率可达968%,故障隔离率达到94%。某型液体火箭发动机实际试车数据结果表明:该故障诊断算法能够准确及时的检测并隔离出故障。     

氢氧内燃机增氧定容燃烧特性研究

航天器携带推进剂有限,氢氧内燃机适宜采用纯氢纯氧+富氢燃烧方式,但目前内燃机纯氢纯氧燃烧缺乏地面试验验证。为此开展氢氧内燃机增氧定容燃烧试验,采用内燃机定容燃烧逐步增氧的技术路线,获得增氧乃至纯氧条件下氢氧内燃机的层流燃烧特性,实现氢氧内燃机高性能高可靠工作。试验结果表明：随着氧气浓度的增大,层流燃烧速度随当量比成倍增加,变化的幅度会逐渐减小;高氧气浓度条件下,层流燃烧速度维持在很高的水平,且随当量比的变化很小。     

飞机电源系统故障诊断方法综述及发展趋势

飞机电源系统是机上一切用电设备的电能来源,其安全性与可靠性至关重要。在环保和高效发展需求的背景下,现代航空工业正在推进以电能为核心的多电/全电飞机技术的研究和应用。电驱动装置和电力电子器件的广泛使用导致飞机电源系统结构的复杂化,对飞机的可靠性、安全性、测试性和维修性提出了更高的要求,研究飞机电源系统的故障诊断技术具有重要意义。首先介绍了飞机电源系统的组成结构和各自功能,概述了飞机电源系统的发展历程,对比了国内外典型电源系统的特征,总结了飞机电源系统中的主要故障模式、故障特点和失效原因,并提出了一种飞机电源健康管理系统的设计架构,然后综述了国内外基于模型和基于数据的故障诊断方法研究进展,从准确度、数据需求量、适用性和实现难易程度等方面评述了各类诊断方法的特点,最后指出了飞机电源系统故障诊断技术面临的挑战和发展趋势。     

基于弹性小波神经网络的故障诊断研究

航空电源系统是机上设备的重要组成部分,任意一个环节出现故障,将会影响整个飞机系统的正常安全运行。针对神经网络收敛速度慢,易陷入局部最小的缺点,将小波神经网络结合弹性BP算法应用到电源系统故障诊断中。训练过程及仿真结果表明：小波神经网络故障诊断算法收敛时间方面表现更优,具有较高故障诊断率。