Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet bases

Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, non-stationary structural vibrations and strong background noises. In this paper, a method based on the flexible analytical wavelet transform (FAWT) possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings. During the route of the proposed method, the proper FAWT bases are constructed via genetic optimization algorithm (GA) based on maximizing the spectral correlated kurtosis (SCK) which is firstly presented and proved to be efficient and effective in indicating interested fault mode. Via using the customized FAWT bases for each interested fault mode, the original vibration measurements are decomposed into fine frequency subbands, and the sensitive subband which enhances the signal-to-noise ratio (SNR) is selected to exhibit the fault signature on its envelope spectrum. The proposed method is tested via simulated signals, and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace, inner-race and roller defects. The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.     

横流中空心锥形喷雾的扩散特性与影响因素

为了更好地理解和认识空心锥形喷雾射流与横向气流的掺混过程，基于可视化实验测量，针对空心锥形喷雾的初始雾化状态、喷射角度和雾化锥角以及横流速度等因素对空心锥形喷雾射流在横流中的扩散特性进行了系统分析。研究结果表明，随着横流速度的提高，流场中对称反旋涡对（CVP）结构变小，但其稳定性及产生的卷吸气流则是先增强而后减小；提高喷雾初始液滴的动量和数流率，均可以增大射流剪切层的贯穿深度和射流尾迹的伸展高度，同时使流场中CVP的涡量强度增大。基于实验测量结果，建立了空心锥形喷雾垂直入射横流条件下掺混流场液滴群CVP结构特征尺寸和剪切层轨迹的预测关联式。另外针对喷嘴雾化锥角和喷射角度的分析表明，当喷雾初始雾化状态相近时，随着雾化锥角的减小，流场中CVP的水平尺度减小但竖直方向尺度增大且结构更为稳定，同时喷雾液滴的贯穿深度增大；相比喷雾垂直于横流入射，当喷嘴以一定角度逆向横流入射时，CVP结构稳定性减弱，流场剪切层涡结构变大且剪切层区域液滴富集现象减弱，射流尾迹紊乱程度增加，反之，则流场剪切层涡拟序结构变小，射流尾迹现象减弱，CVP结构变小。     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

Fault mode probability factor based fault-tolerant control for dissimilar redundant actuation system

This paper presents a Fault Mode Probability Factor (FMPF) based Fault-Tolerant Control (FTC) strategy for multiple faults of Dissimilar Redundant Actuation System (DRAS) composed of Hydraulic Actuator (HA) and Electro-Hydrostatic Actuator (EHA). The long-term service and severe working conditions can result in multiple gradual faults which can ultimately degrade the system performance, resulting in the system model drift into the fault state characterized with parameter uncertainty. The paper proposes to address this problem by using the historical statistics of the multiple gradual faults and the proposed FMPF to amend the system model with parameter uncertainty. To balance the system model precision and computation time, a Moving Window (MW) method is used to determine the applied historical statistics. The FMPF based FTC strategy is developed for the amended system model where the system estimation and Linear Quadratic Regulator (LQR) are updated at the end of system sampling period. The simulations of DRAS system subjected to multiple faults have been performed and the results indicate the effectiveness of the proposed approach.     

Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine

Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.     

Fault self-repair strategy based on evolvable hardware and reparation balance technology

In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.     

流场可压缩性对涡相互作用影响的数值研究

涡相互作用作为冲压发动机喷注装置的典型抽象流动现象,研究其可压缩性影响对于认识包含化学反应的真实燃料喷射场具有一定基础理论价值。基于经过数值验证的可压缩Navier-Stokes算法与压力泊松方程初始条件设置方法研究流场可压缩性对涡相互作用演化过程的影响。结果表明,以较高涡旋马赫数表征的可压缩性在改变涡对形态的同时,具有延缓涡旋相互靠近,迟滞融合进程的作用。关于涡对系统开始融合的临界条件,可压缩相互作用开始的临界展弦比与无量纲时间相比于低速涡对明显提高。为在无量纲时间意义下统一不同马赫数涡对相互作用的进程,从涡心密度随时间变化规律出发在不可压涡对特征时间的基础上,初步构建了考虑可压缩性的时间尺度修正关系。     

送粉方式对等离子喷涂NiCrAlY/ Al2 O3涂层介电性能的影响

以内送粉和外送粉两种方式微弧等离子喷涂工艺制备了NiCrAlY/Al_2O_3复合涂层,分析了送粉方式对涂层相组成、微观结构和介电性能的影响。结果表明:与外送粉相比,内送粉方式沉积的涂层具有较高的沉积效率和较低的孔隙率。由于喷涂过程中α-Al_2O_3颗粒完全熔融,内送粉喷涂所得到涂层主要为γ/γ′和γ-Al_2O_3相,并且涂层结构致密,NiCrAlY颗粒分布均匀。介电性能测试表明,以外送粉方式制备的涂层复介电常数实部和虚部几乎不随频率发生变化。而以内送粉方式喷涂的涂层复介电常数实部和虚部随频率的增加而降低,呈现明显的频散现象。     

永磁同步电机无传感器转子位置观测器研究

永磁同步电机的运动是一个强耦合非线性动态过程,旋转高频电压注入下 的电机模型存在建模误差,数据采集存在测量噪声和系统噪声,采用传统的线性控制理 论难以达到要求。提出了以不依赖于准确数学模型的广义预测控制算法为基础的转子位 置观测器,可有效提高转子位置检测精度,增强抗干扰能力。仿真实验结果表明,在存 在建模误差和噪声的情况下,基于广义预测控制算法位置观测器的旋转高频注入法可准 确追踪转子位置。     

基于SINS/GPS/CNS的机载综合导航系统故障诊断方法研究

传感器是导航系统中的重要部件,传感器故障容错性的分散化滤波,对提高系统的可靠性具有重要意义.以SINS/GPS/CNS组成的组合导航系统为研究对象,采用联邦滤波和方差交叉滤波相结合的方法,实现了对传感器故障具有容错性的分散化滤波,对导航系统的精度和容错性进行分析.仿真结果表明,将分散化滤波方法用于多个传感器组成的组合导航系统,不但具有精度高的特点,而且由于具有信息的冗余,整个系统具有较好的容错能力,可以提供更加完善、精确地反映运载体运动的导航信息.