一种基于微多普勒的爆震检测新方法

爆震的检测对于发动机的安全性和使用寿命有着重要的意义.首先建立了发动机缸体的雷达回波信号模型,分析了正常燃烧和爆震现象发生时缸体振动信号的微多普勒特征,并利用SPWV时频分析方法提取了该信号的微多普勒特征,最后通过仿真验证了利用微多普勒特征检测爆震现象的实时性和有效性.     

Measurement of moment of inertia based on hilbert transform

A measurement model based on torsion pendulum was established,in which nonlinear damping and nonlinear restoring force were considered.The calculation method of the moment of inertia was based on Hilbert transform.The motion of torsion pendulum showed the time-frequency characteristics due to the nonlinear factors,which were validated by the experimental data.The analytical signal was formed by Hilbert transform of the angular displacement signal of the test object.The moment of inertia can be computed by the instantaneous undamped natural frequency with Hilbert transform.Prior to the implementation of Hilbert transform,the empirical mode decomposition was used to filter the experimental signal.The moment of inertia of the test object was measured by the torsion pendulum system.The experimental results show that the relative measurement error of the moment of inertia was within 0.7%,which indicated the validity of the measurement method.     

经验模态分解的分段二次算法

A new algorithm, named segmented second empirical mode decomposition （EMD） algorithm, is proposed in this paper in order to reduce the computing time of EMD and make EMD algorithm available to online time-frequency analysis. The original data is divided into some segments with the same length. Each segment data is processed based on the principle of the first-level EMD decomposition. The algorithm is compared with the traditional EMD and results show that it is more useful and effective for analyzing nonlinear and non-stationary signals.     

基于EMD的汽车轴重估计

Dynanfic forces are the main factor that influences the axle weight measurement accuracy of moving vehicle. Empirical mode decomposition （EMD） is presented to separate the dynamic forces contained in the axle weight signal. The concept and algorithm of EMD are introduced. The characteristic of the axle weight signal is analyzed. The method of judging pseudo intrinsic mode function （pseudo-IMF） is presented to improve the weighing accuracy. Numerical simulation and field experiments are conducted to evaluate the performance of EMD. The result shows effectiveness of the proposed method. Maximum weighing errors of the front axle, the rear axle and the gross weight at the speed of 15 km/h or lower are 2.22%, 6.26% and 4.11% respectively.     

基于双重对称延拓的HHT端点效应抑制方法

经验模态分解( empirical mode decomposition,EMD)存在端点飞翼的固有问题,使信号两端出现扭曲失真。为抑制EMD端点效应,文章提出双重对称延拓法,以端部数据对称延拓作为首次延拓,以极值点对称延拓作为二次延拓,该方法可同时实现EMD分解和Hilbert变换两阶段端点效应的抑制。仿真信号和地震响应的工程算例通过IMF分量对比、瞬时频率对比,以及整体正交性、相关系数等指标的对比,验证了该方法具有良好的端点效应抑制效果,同时还能改善IMF分量之间的正交性,并节约计算时间。     

基于EEMD和LS-SVM的癫痫脑电信号识别

针对癫痫脑电(EEG)信号的非平稳性和非线性,提出一种基于集合经验模式分解(EEMD)提特征并利用最小二乘支持向量机(LS-SVM)的脑电信号分类方法。首先利用EEMD将EEG信号分成多个经验模式分量,得到各阶本征模式分量(IMF),然后提取有效特征,最后用LS-SVM对其进行分类,实验结果表明,该方法对癫痫发作间歇期和发作期EEG的提特征后分类识别正确率达到98%。     

Multi-Body Dynamics Analysis and Low Noise Optimization of X6170ZC Diesel

Thelevel of vibration and noiseis animportant estima-tionindexoninternal combustionengines .As vibrationandnoise legislations are continually introduced and progres-sivelyrestricted,lowerlevel noise becomesincreasinglyim-portant .The traditional design pe…     

Applying sub-band energy extraction to noise cancellation of ultrasonic NDT signal

In ultrasonic non-destructive tests, the echo signal at the flaw is highly complex due to the interference of multiple echoes with random amplitudes and phases, and is disturbed by all kinds of noises, such as thermal noise, digitalization noise, and structure noise. In this paper, the ultrasonic signal was decomposed by empirical mode decomposition （EMD） to obtain the intrinsic mode function （IMF） components according to ultrasonic defect echo signals occuring at the corresponding time, and the energy of the ultrasonic signal was concentrated. The IMF component selection criterion based on sub-band energy extraction was proposed to extract the ultrasonic signal component accurately and automatically from IMF components. When the selected IMF components were filtered by a band pass filter, the signal-to-noise ratio （SNR） was enhanced greatly.     

基于可变控制的车辆发动机均质压燃技术

均质压燃（HCCI）能够使发动机同时保持较高的动力性能和燃油经济性,而且能有效降低发动机的NOx和PM排放,是一种克服传统的汽油机和柴油机缺点、集二者优点于一体的新的燃烧模式。由于其突出的优越性已成为目前世界范围发动机领域的研究热点,应用前景广阔,但由于HCCI的燃烧特点以及目前相关技术的约束,使其实用化进程仍存在不少问题。本文对HCCI燃烧方式和过程进行了介绍,详细分析了制约和影响HCCI燃烧方式的关键因素,针对HCCI的特点及其燃烧始点和燃烧过程控制的关键问题,提出了改变空气/燃料混合气特性的可变控制技术解决方案,为HCCI技术的实用化进程提供理论指导,为尽快实施HCCI燃烧方式指出了技术方向。     

改进EEMD算法在缸盖振动信号降噪中的应用研究

针对常规降噪方法应用于柴油机缸盖振动信号降噪时,自适应差且需要根据噪声环境人为调整参数的问题,在传统EEMD算法基础上提出一种改进的EEMD降噪算法,并将其应用于柴油机缸盖振动信号处理。首先对原始信号进行预处理,其次利用总体经验模态分解（EEMD）算法在非线性、非平稳信号处理时的自适应特性,分解原始信号得到各阶本征模态分量,经Savitzky-Golay平滑滤波,再将噪声占主导的高频分量进行阈值去噪,最后得到干净的本征模态分量进行重构。仿真实验和实测结果表明,在输入信号12dB的多种输入信号工况下,改进EEMD算法去噪后信噪比为17.1,比现有去噪方法提升14%。     

Application of Improved LMD,SVD Technique and RVM to Fault Diagnosis of Diesel Valve Trains

Targeting the non-stationary characteristics of diesel engine vibration signals and the limitations of singular value decomposition(SVD) technique, a new method based on improved local mean decomposition(LMD), SVD technique and relevance vector machine(RVM) was proposed for the identification of diesel valve fault in this study. Firstly, the vibration signals were acquired through the vibration sensors installed on the cylinder head in one normal state and four fault states of valve trains. Secondly, an improved LMD method was used to decompose the non-stationary signals into a set of stationary product functions(PF), from which the initial feature vector matrices can be formed automatically. Then, the singular values were obtained by applying the SVD technique to the initial feature vector matrixes. Finally, slant binary tree and sort separability criterion were combined to determine the structure of multi-class RVM, and the singular values were regarded as the fault feature vectors of RVM in the identification of fault types of diesel valve clearance. The experimental results showed that the proposed fault diagnosis method can effectively extract the features of diesel valve clearance and identify the diesel valve fault accurately.     

Multidimensional modeling of Dimethyl Ether （DME） spray combustion in DI diesel engine

INTRODUCTION The use of dimethyl ether (DME) as an alterna-tive fuel appears to be a promising approach for si-multaneously minimizing NOx and soot emissionfrom conventional diesel engines. The lowself-ignition temperature of 508 K and the high oxy-gen content of 34.8 percent (mass fraction) are twomajor factors characterizing low soot and unburnedtotal hydrocarbon (THC) emissions. Since the firstintroduction of the concept by Sorenson and Mik-kelsen (19…     

Effects of Exhaust Gas Recirculation on the Homogeneous Charge Combustion Process of n-Heptane at Different Load Conditions

Effects of exhaust gas recirculation （ EGR） on homogeneous charge combustion of n-heptane was studied through simulation and experiment. Experiments were carried out in a single cylinder, four-stroke, air cooled engine and a single cylinder, two-stroke, water cooled engine. In the four-stroke engine, experiments of the effects of EGR were examined using heated N2 addition as a surrogate for external EGR and modifying engine to increase internal EGR. The ignition timing was sensitive to EGR due to thermal and chemical effects. EGR or extra air is a key factor in eliminating knock during mid-load conditions. For higher load operation the only way to avoid knock is to control reaction timing through the use of spark ignition. Experimental and modeling results from the twostroke engine show that auto-ignition can be avoided by increasing the engine speed. The twostroke engine experiments indicate that high levels of internal EGR can enable spark ignition at lean conditions. At higher load conditions, increasing the engine speed is an effective method to control transition from homogeneous charge compression ignition （ HCCI） operation to non-HCCI operation and successful spark ignition of a highly dilute mixture can avoid serious knock.     

Characteristics of HCCI engine operation for additives,EGR, and intake charge temperature while using iso-octane as a fuel

This work investigates the effects of exhaust gas recirculation (EGR) and operation parameters including engine speed, equivalence ratio, coolant-out temperature, and intake charge temperature on the basic characteristics of a single-cylinder homogeneous charge compression ignition (HCCI) engine powered with reformulated iso-octane fuels. The running range of iso-octane HCCI engine can be expanded to lower temperature and more load by adding di-tertiary butyl peroxide (DTBP) in the fuel. The combustion timing advances with the increase of DTBP concentrations, coolant temperature and equivalence ratio. The effects of EGR on the combustion and emissions are remarkable when the EGR rate is higher than 25%, and the combustion phase is sharply postponed and the UHC and CO emissions deteriorate. The intake charge temperature has a moderate effect on combustion and emissions when it is lower than 35°C; but the combustion timing advances, the combustion duration shortens, and sometimes it leads to knock combustion when the intake charge temperature increases to above 35°C.     

Fault diagnosis of valve clearance in diesel engine based on BP neural network and support vector machine

Based on wavelet packet transformation(WPT), genetic algorithm(GA), back propagation neural network(BPNN)and support vector machine(SVM), a fault diagnosis method of diesel engine valve clearance is presented. With power spectral density analysis, the characteristic frequency related to the engine running conditions can be extracted from vibration signals. The biggest singular values(BSV)of wavelet coefficients and root mean square (RMS)values of vibration in characteristic frequency sub-bands are extracted at the end of third level decomposition of vibration signals, and they are used as input vectors of BPNN or SVM. To avoid being trapped in local minima, GA is adopted. The normal and fault vibration signals measured in different valve clearance conditions are analyzed. BPNN, GA back propagation neural network (GA-BPNN), SVM and GA-SVM are applied to the training and testing for the extraction of different features, and the classification accuracies and training time are compared to determine the optimum fault classifier and feature selection. Experimental results demonstrate that the proposed features and classification algorithms give classification accuracy of 100%.     

基于 EMD-PSO-ELM 算法的大坝变形预测研究

基于极限学习机（ELM）构建的大坝变形预测模型易受连接权值、隐含层阈值及隐含层节点数影响,为获取更优的形变预测值,并改善模型预测可靠性,构建一种基于 EMD-PSO-ELM 算法,考虑时效、温度、水位等多因素的大坝变形预测模型。该模型首先从时频分析出发,利用经验模态分解（EMD）将变形时间序列分解成具有不同频率特征的分量|然后利用 PSO-ELM 模型解求形变预测值,重构获得大坝形变趋势。实验结果表明,融合时效、温度、水位等多因素的 EMD-PSO-ELM 大坝变形预测模型残差均方根误差为 1.83mm,平均绝对误差为 1.57mm,平均绝对百分比误差为 1.79%,比 ELM 模型与 EMD-ELM 模型相关误差值更小,在大坝变形预测方面性能更优。     

乙醇-柴油发动机可调参数对动力性影响研究

乙醇柴油的不同配比、供油提前角、喷油压力、喷油泵柱塞直径及行程燃烧室的型式等参数的调整,对乙醇柴油混合燃料的柴油机动力性、经济性、排放指标等有重要的影响．参数调整后的乙醇柴油发动机经济性和排放指标皆优于纯柴油发动机,动力性略低于纯柴油发动机．     

基于ESMD与SVM的电能质量混合扰动识别

针对实际电能质量扰动种类繁多、扰动信号差异不明显、存在多种混合扰动,导致识别电能质量非常困难的情况,提出一种基于极点对称经验模式分解方法（ESMD）和支持向量机（SVM）的电能质量混合扰动信号分类识别新方法。首先,对加入白噪声的混合扰动信号利用小波软阈值去噪处理|其次,利用ESMD将信号分解为不同信号分量,对每类扰动的不同信号分量分别提取样本熵和互样本熵特征值,所有分量特征值构成特征向量|最后利用SVM对扰动信号特征向量进行分类和混合扰动识别。研究表明,该方法对混合扰动识别正确率很高,是一个有效的方法。     

柴油机净化新技术综述

柴油机是最有效的内燃动力装置,高速载货汽车、城市客车和工业设施几乎都采用柴油机,而重型柴油机的尾气是烟雾和酸雨的主要来源。因此,改进和开发汽车尾气控制技术就成为汽车设计者们一大攻关问题,文章就此问题进行阐述。     

Comparison of different techniques for time-frequency analysis of internal combustion engine vibration signals

In this study, we report an analysis of cylinder head vibration signals at a steady engine speed using short-time Fourier transform (STFT). Three popular time-frequency analysis techniques, i.e., STFT, analytic wavelet transform (AWT) and S transform (ST), have been examined. AWT and ST are often applied in engine signal analyses. In particular, an AWT expression in terms of the quality factor Q and an analytical relationship between ST and AWT have been derived. The time-frequency resolution of a Gaussian function windowed STFT was studied via numerical simulation. Based on the simulation, the empirical limits for the lowest distinguishable frequency as well as the time and frequency resolutions were determined. These can provide insights for window width selection, spectrogram interpretation and artifact identification. Gaussian function windowed STFTs were applied to some cylinder head vibration signals. The spectrograms of the same signals from ST and AWT were also determined for comparison. The results indicate that the uniform resolution feature of STFT is not necessarily a disadvantage for time-frequency analysis of vibration signals when the engine is in stationary state because it can more accurately localize the frequency components excited by transient excitations without much loss of time resolution.