发动机经验故障方程的建立与求解

本文提出了根据发动机故障样本建立发动机故障方程并利用最优化方法(主特征量模型)求解的故障诊断方法。经验故障方程是不同于发动机小偏差方程的另一类故障方程,它为发动机故障诊断提供了一条简便易行的途径,并且使发动机故障诊断范围扩展到气路分析方法难以适用的场合。文申讨论了经验故障方程的建立方法,求解方法和应用特点,给出了利用经验故障方程进行发动机故障诊断的实例。     

V-22 mechanical diagnostic design approach

The requirements and diagnostic applications for the V-22 tiltrotor aircraft are used to demonstrate the unique requirements of mechanical system diagnostic design. The rationale for the approach selected is explored, and it is shown how the mechanical system diagnostic requirements affect the avionics architecture and performance requirements. It is concluded that, in light of the underdeveloped nature of mechanical diagnostics technology and the extended time required for a given mechanical diagnostic design to mature, future avionics system designs need architecture that is adaptable enough to accommodate the evolving mechanical diagnostics     

Method of determining the maximum permissible values for diagnostic signs of helicopter transmission units operational status

A method of determining the maximum permissible values for diagnostic signs, being an integral part of health and usage monitoring systems (HUMS) of the helicopter transmission units, has been developed based on a probabilistic approach.     

A GPA diagnostic system foraeroengine applications

In this research, a GPA(Gas Path Analysis) diagnostic system enhanced with GPA Index is described for gas path sensor and component fault diagnosis.A method of measurement correction is used in order that the measurement data obtained at un-standard ambient and operating conditions can be used for diagnostic analysis.The developed diagnostic system has been implemented into a Cranfield University gas turbine performance and diagnostic analysis software PYTHIA for gas turbine performance degradation analysis.The developed method and software have been applied to a model aero gas turbine engine to test the effectiveness of the system.The analysis shows that the developed diagnostic system can diagnose degraded sensor and components effectively using performance deviation measured at un-standard ambient and operational conditions.Theoretically, the idea of the diagnostic approach can be applied to different gas turbine engines.      

基于模糊粗集的航空发动机特征参数提取算法

提取发动机性能状态的特征参数,是提高发动机故障识别正确率和可靠性的必要条件.针对实际航空发动机故障参数所具有的模糊和连续性特点,提出了一种基于模糊粗糙集的特征参数提取算法,并应用到某型航空发动机故障识别.研究结果表明:属性约简的核则为导致发动机故障的特征参数,以此特征参数进行故障诊断,可保证较高的诊断精度;同时,该算法的抗干扰性提高了整个系统故障识别的正确率.该算法可用于航空发动机故障分类、故障诊断以及状态监控.      

基于分层传递系统模型的航天器故障诊断方法

 针对传统的传递系统模型在航天器自主诊断系统中只能表示单一粒度诊断知识,知识表示的完备性差,导致诊断结果的分辨率不高,且诊断系统执行效率低的问题,提出了分层传递系统模型和诊断方法。为了保证不同粒度诊断知识的完备性表示,将系统模型按不同粒度和结构关系进行分层。通过自顶向下的递归搜索,先监测系统异常,再匹配故障类型,逐层缩小搜索空间,最终找出故障候选集和故障的层次关系。同时为了减小计算规模,在诊断过程中引入了分离策略,降低实时诊断计算量。应用该方法建立了某卫星测控分系统模型并进行故障仿真,结果表明该方法可以增加模型知识表示的完备性,并能有效提高诊断效率和结果的分辨率。     

A Diagnostic Tree Approach for Fault Cause Identification in the Attitude Control Subsystem of Satellites

Space and Earth observation programs demand stringent guarantees ensuring smooth and reliable operations of space vehicles and satellites. Due to unforeseen circumstances and naturally occurring faults, it is desired that a fault-diagnosis system be capable of detecting, isolating, identifying, or classifying faults in the system. Unfortunately, none of the existing fault-diagnosis methodologies alone can meet all the requirements of an ideal fault- diagnosis system due to the variety of fault types, their severity, and handling mechanisms. However, it is possible to overcome these shortcomings through the integration of different existing fault-diagnosis methodologies. In this paper, a novel learning-based, diagnostic-tree approach is proposed which complements and strengthens existing efficient fault detection mechanisms with an additional ability to classify different types of faults to effectively determine potential fault causes in a subsystem of a satellite. This extra capability serves as a semiautomatic diagnostic decision support aid to expert human operators at ground stations and enables them to determine fault causes and to take quick and efficient recovery/reconfiguration actions. The developed diagnosis/analysis procedure exploits a qualitative technique denoted as diagnostic tree (DX-tree) analysis as a diagnostic tool for fault cause analysis in the attitude control subsystem (ACS) of a satellite. DX-trees constructed by our proposed machine-learning-based automatic tree synthesis algorithm are demonstrated to be able to determine both known and unforeseen combinations of events leading to different fault scenarios generated through synthetic attitude control subsystem data of a satellite. Though the immediate application of our proposed approach would be at ground stations, the proposed technique has potential for being integrated with causal model-based diagnosis and recovery techniques for future autonomous space vehicle missions.     

基于虚拟仪器的无人机故障诊断系统设计

介绍了一种基于虚拟仪器的无人机故障诊断系统,给出了系统的硬件及软件组成,并就故障诊断的原理及软件实现方法做了介绍。该系统可方便实现对无人机现场故障的检测和诊断,具有良好的使用性能和价值。     

Knowledge Acquisition for ATE Diagnosis

An applied intelligence program for ATE fault diagnosis shows promise as an effective method to reduce mean time to repair (MTTR). The types of knowledge required by an intelligent diagnostic for VLSI test systems, the resources needed to derive that knowledge, the approach implemented to organize it, and the final form of the knowledge representations which resulted from our work are discussed in this paper.     

基于卡尔曼滤波器和遗传算法的航空发动机性能诊断

以某型涡扇发动机为研究对象,构建了基于卡尔曼滤波器和遗传算法的航空发动机性能诊断方法。卡尔曼滤波器根据发动机可测参数偏离额定特性时的变化量,对发动机性能参数进行了估计。当传感器存在测量偏差时,会使滤波器估计结果偏离真实情况。遗传算法以机载模型输出与发动机测量参数之间的误差最小为目标,通过优化计算,找出存在测量偏差的传感器,确定其偏差,并最终消除测量偏差对性能诊断的影响。     

Using built-in-test to reduce TPS run times and improve TPSreliability

This paper addresses using information derived from Built-in-Test (BIT) to fault diagnose Units Under Test (UUTs), wherever possible. This philosophic approach to diagnostic testing is not new. It has been studied over the past 20 years under the visor of “Integrated Diagnostics”, but it has yet to be truly implemented in a “real life” military diagnostic test environment. The mindset of Test Program Set design engineering, along with customer and contractor management alike, remains “complete diagnostic testing based upon single catastrophic component failure modes”. If we are to generate cost efficient Test Program Sets (TPSs) under reduced military budget constraints, this will have to change! The test engineer must be encouraged to use methodologies to speed up development time and decrease TPS run times. Using present technology, this is possible now, and as the technology matures, will become a truly viable approach in the future. For the purpose of this paper, the author relies heavily on his extensive US Navy Automatic Test Equipment (ATE) and Test Program Set (TPS) experience, as well as on previous studies performed on using BIT to fault diagnose Unit Under Test failures on US Naval Air weapon systems     

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.     

Sensor/actuator fault diagnosis based on statistical analysis of innovation sequence and Robust Kalman Filtering

In this paper, an approach to detect and isolate the aircraft sensor/actuator faults affecting the mean of the Kalman filter innovation sequence is presented. The effects of the sensor and actuator faults in the innovation process of the channels are investigated, and a decision approach to isolate the sensor and actuator faults is proposed. When a Kalman filter is used, the decision statistics change regardless of whether the fault is in the sensors or in the actuators, whilst when a Robust Kalman Filter (RKF) is used, it is easy to distinguish the sensor and actuator faults. A novel feature of this diagnostic method is that the innovation sequence based fault isolation algorithm has been presented and hence, the sensor/actuator fault detection and isolation problem has been solved. The categories (or classes) of the likely faults are not demanded. The statistical characteristics of the system are not required to be known after the fault has occurred. In the simulations, the longitudinal dynamics of an aircraft control system are considered, and the detection and isolation of pitch rate gyro faults and actuator faults affecting the mean of the innovation sequence are examined.     

Integrating diagnostic knowledge

The use of artificial intelligence technique to access, analyze, and integrate different types of knowledge under a single diagnostic concept is described. Repair statistics and field experience are handled by an empirical knowledge (shallow reasoning) diagnostic system in order to retain the experience of expert test personnel. Computer-aided-design knowledge is handled by model-based (deep reasoning) diagnostic systems in order to extract diagnostics directly from design data. Combining these approaches overcomes limitations of the individual techniques and provides a more powerful diagnostic system. The Westinghouse expert diagnostic system is considered as an example     

航空发动机全权限数控系统研究和试飞验证

以某型发动机为控制对象,研究航空发动机全权限数字电子控制系统(FADEC)。对数控系统的总体结构、控制规律、故障诊断及余度设计、电子控制器、液压机械装置、控制软件开发等关键技术分别进行了讨论。通过试飞,验证了该数控系统功能和性能及其关键技术。试飞结果表明,使用全权限数字电子控制系统取代传统的液压机械调节器不仅扩展了发动机控制系统的控制功能,同时也更有效地发挥了航空发动机的性能,改善了发动机的操纵性、维护性和可靠性。      

传感器测量偏差下的航空发动机智能性能诊断

以某型涡扇发动机为研究对象, 构建了基于神经网络的航空发动机智能性能诊断方法, 讨论了测量噪声及测量偏差对诊断结果的影响及其处理方法.建立一簇并行的神经网络组和发动机模型, 通过比较各模型输出与发动机测量参数之间的误差, 判断传感器是否存在测量偏差.仿真结果表明, 该方法能有效消除测量噪声, 准确判断并隔离有测量偏差的传感器, 得出正确的发动机性能诊断结果.      

Next generation functional test program development system

While superior-quality functional board test has been a goal for most high reliability electronics manufacturers, the time and effort for generating such test programs using today's tools and processes makes this difficult to achieve in a cost effective manner. This paper will introduce a revolutionary approach to functional board test program development that combines the comprehensiveness of software-based simulation with the speed and simplicity of hardware emulation. The result is a functional Test Program Set development system that can produce high fault coverage, diagnostic test programs in a fraction of the time it takes using traditional techniques, and at a lower unit cost. In this paper we will first provide a brief background on the strengths and weaknesses of current software and hardware TPS development techniques-simulation hot mock-up. Next, the new approach is described in detail and contrasted against the existing techniques. Finally, actual experience to date using a prototyped system is presented     

Generic Integrated Maintenance Diagnostics

Maintenance Support for a weapon system involves both preventive and corrective maintenance actions. Preventive maintenance is normally associated with mechanical equipment, and requires prognostic maintenance techniques to predict failures before they occur. Corrective maintenance is more closely associated with electronic equipment, and requires diagnostic maintenance techniques to detect and isolate failures after they occur. To pursue a systems approach to weapon system maintenance using both prognostics and diagnostics, the Air Force has initiated a program entitled, ``Generic Integrated Maintenance Diagnostics (GIMADs)'. This paper provides insight into the GIMADS program at Aeronautical Systems Division.     

民航发动机远程故障诊断若干关键技术研究

本文提出的民航发动机远程故障诊断技术将Internet网络技术与民航发动机故障诊断技术有效地结合起来,旨在将民航发动机的维护和故障诊断手段提升到远程的网络环境,以极大提高故障诊断的水平和时效性。本文从工程应用角度出发,对其中的几个关键技术问题进行了讨论。首先分析了民航发动机故障诊断的技术现状,提出了民航发动机远程故障诊断系统的结构体系。提出一种诊断设备网络化的设计思想,即采用上下位机的结构和COM组件技术,实现远程操作、状态监视和控制。采用COM组件技术和网络数据库技术实现了在Web服务器上的知识的存储与推理。分别基于NI的Labview/GWebServer和DataSocket技术,开发了两种多功能的远程故障诊断的协同工作环境(CSCW)。      

口径近场的特征谱

 提出口径近场特征谱的概念,以描述口径设计近场特征。特征谱包括角域谱和时域谱,分别定义为口径近场区空域场和频域场在角域和时域的变换。理论分析和计算结果表明,特征谱可以在角域和时域上分离有限大口径的直达波和绕射波,因而可以用来描述口面尺寸、形状和场分布等条件改变时绕射场的相对变化,这对紧缩场设计具有参考价值。基于口面场卷积法,计算、比较了限度为5 m×5 m圆口径和方口径近场在X波段特征谱分布。并导出：口径近场角谱为口径场角谱和网络响应函数角谱的乘积,网络响应函数等效于一个空间角谱滤波器。