基于储罐底板腐蚀声发射监测技术的信号能量分析

原油储罐底板在运行中容易发生腐蚀,声发射监测技术通过分析声发射信号来判断底板腐蚀状态,为此需确定腐蚀过程中腐蚀信号的能量来源。根据声发射特点,利用表面能与电化学能推算出金属腐蚀的能量公式,并且利用MATLAB根据能量公式分析金属腐蚀声发射信号能量随腐蚀时间的变化关系。根据分析的变化关系曲线得出金属腐蚀电化学能量与表面能在金属腐蚀中所占比重有较大差别,说明金属腐蚀声发射信号能量的主要来源为电化学腐蚀产生的能量。对通过腐蚀速率来判断底板腐蚀状态具有一定的理论指导。     

金刚石砂轮磨削性能退化评估

为了提取高精度磨削干涉中的声发射信号特征,实现砂轮磨削性能退化评估,针对熔石英开展全寿命周期金刚石砂轮磨削实验,基于小波包分析确定砂轮磨损敏感频段为低频段,然后计算声发射信号在低频段的归一化能量占比,再利用主成分分析对能量占比进行特征降维获得单值特征,利用该单值特征绘制砂轮磨削性能退化曲线。研究结果表明,监测特征能够清晰反映砂轮初期磨损、正常磨损和过度磨损三个阶段,且监测结果不受加工参数影响;砂轮磨削材料破裂尺度与声发射频率具有一定关系,伴随砂轮磨损的加剧,较大尺度破裂的比例上升,造成65kHz以下低频段特征的能量占比增大,监测特征显著增加,磨粒崩碎产生新的切削刃,砂轮的去除能力有所改善,监测特征数值回落,但是,不同样本的声发信号频谱差异性显著增加,说明砂轮加工状态不稳定,不利于精密与超精密加工中维持稳定质量的要求。砂轮形貌图像的白像素占比变化曲线验证了声发射特征对砂轮磨损状态判断的正确性。     

基于声发射分析的磨料流光整加工在线检测试验研究

针对磨料流光整加工中孔类零件表面粗糙度在线检测困难的问题,将声发射检测技术应用到了磨料流加工中。通过研究磨料流加工过程中的声发射源与声发射特性,利用参数分析法得到了波形特征参数随加工时间的变化曲线,建立了声发射信号的能量及振铃计数与零件表面粗糙度之间的关系;根据幂率流体本构方程计算了壁滑速度,分析了壁滑速度对声发射信号能量的影响。研究结果表明:声发射信号能量和振铃计数随着表面粗糙度的增大而增大,且两者随表面粗糙度的变化规律基本相同;表面粗糙度是声发射信号发生变化的主要原因,随着表面粗糙度的减小,即使增大壁滑速度,声发射信号强度也会降低;声发射可用于磨料流加工孔类零件表面粗糙度的在线检测。     

基于小波能谱系数的风力机疲劳裂纹特征

提出了风力机叶片裂纹扩展声发射信号的优化小波重分配尺度谱及小波能谱系数相结合的分析法。基于Shannon熵理论计算裂纹扩展声发射信号的重分配尺度谱小波基函数带宽参数,得到最适合裂纹声发射信号的Morlet小波基函数。用优化后的小波基函数计算重分配尺度谱,获得裂纹扩展特征成分在时间尺度平面的高幅值能量分布,利用特征能谱系数表征其重分配尺度谱的特征。实验结果表明,该方法有良好的时频聚集性和抗噪能力,实现了风力机叶片裂纹扩展声发射信号的时频特征提取,得到了能谱系数作为特征向量表示信号特征。该方法可用来实现风力机叶片在复杂环境中的模式识别。     

裂缝扩展声发射有限元模拟及其信号时频分析

根据定量地震学中的矩张量理论，建立了裂缝扩展声发射源的力学模型及有限元模型，通过有限元计算得到裂缝扩展声发射的波形信号。利用小波变换对不同裂缝深度的声发射波形信号进行时频分析，得到不同裂缝深度的声发射波形信号的时频特征。通过研究声发射信号中零阶反对称模式成分（A0）和零阶对称模式成分（S0）的能量比，发现声发射信号的能量比EA0／ES0随裂缝深度变化具有一定规律性，能够通过能量比判断裂缝扩展的深度。     

基于声发射信号的钢桶泄漏特性试验研究

基于企业验漏需求,设计搭建了钢桶泄漏试验台和钢桶泄漏声发射信号检测系统。通过实验研究了不同泄漏工况下,钢桶泄漏产生的声发射信号特性。试验表明钢桶泄漏声发射信号频域特征出现在90~100k Hz。通过小波包分解,提取了90~100k Hz频段的能量作为泄漏特征。得到了钢桶的泄漏能量特征和信号均方根值(RMS)随泄漏孔径尺寸、钢桶内部加压压力和声发射传感器位置的变化规律。建立了基于钢桶声发射信号的泄漏检测规则,为实际应用过程中选择泄漏特征参数、加压压力和选择传感器位置及个数提供了参考。     

基于声发射技术的拉深过程中润滑状态分析

采用发射技术监测了拉深过程中的润滑状态.在干摩擦和润滑脂润滑下,进行了拉深成形实验,并分析了不同润滑状态下拉深过程中声发射信号的能量、振铃计数、信号幅度等参数的变化规律.结果表明,拉深中产生声发射信号对润滑状态非常灵敏,随着润滑状态改善,拉深过程中产生的声发射信号能量、振铃计数、信号幅度参数等均呈下降趋势;通过对声发射信号分析可以判断拉深件的摩擦状况,即将声发射技术引入金属板材拉深中的摩擦状态的监测是可行的.     

基于Elman神经网络的刀具磨损状态识别技术

由于刀具磨损声发射信号的能量分布与刀具磨损状态密切相关,可以利用谐波小波包方法提取刀具磨损声发射信号的特征能量,对各频段能量做归一化处理,与切削三要素组成特征向量输入到Elman神经网络,通过神经网络判别刀具磨损状态。实验结果表明,刀具磨损产生的声发射信号频率主要集中在10Hz~130k Hz之间,将谐波小波包和Elman神经网络结合的方法可以有效地识别刀具磨损状态。     

基于声发射技术的螺栓状态监测研究

利用声发射技术监测螺栓工作过程中的状态变化,对声发射检测信号进行时域、频域及小波分析。结果表明,螺栓由于塑性变形和断裂引起的声发射频率明显区别于振动、撞击、摩擦等所产生的频率,验证了声发射技术用于连接螺栓状态辨识的可行性。     

声发射检测技术在压力容器应力腐蚀检测中的应用

采用声发射检测技术对装有FeCl_3溶液的小型压力容器出现的应用腐蚀问题进行检测研究。检测结果显示,该小型压力容器采用的Q345R材料凯塞尔效应明显,一次压力循环声发射信号撞击数、幅度和能量较高。表明声发射检测技术可根据声发射信号强度及变化来对设备的运行状况进行判断,实现对压力容器的应力腐蚀过程进行有效监控。     

Ring wear monitoring in IC engines: an acoustic emission approach

Monitoring the condition of the engine compression ring in an engine operation is very important since it affects the engine performance. One of the most promising ring wear monitoring methods is based on the analysis of acoustic emission (AE) signals, which is an extremely powerful technique that can be deployed in a wide range of applications of non-destructive testing [Vallen Systeme (2000)]. This technique is already used for monitoring tool wear almost in all machining operations, but in this study, the AE signals were applied for monitoring ring wear in internal combustion (IC) engines. The AE signals generated in the ring sliding zone are very sensitive for correlation with ring wear, which in turn affects ring performance. This study was carried out with a single compression ring mounted on the piston. The AE signals were analyzed by considering signal parameters such as ring down count and RMS voltage [Krzysztof Jemielniak (2000) J Mater Process Technol 4752:1–6]. Analysis showed that the AE signal technique is applicable for ring wear monitoring in IC engines.     

Swirl effect on the spray characteristics of a twin-fluid jet

In the liquid fuel combustion chamber, employed fuel must be atomized before being injected into the combustion zone. Therefore, the complete fuel atomization is the most important condition for the combustion efficiency. The atomization quality strongly affects the combustion performance, exhaust pollutant emissions, and flame stability. Therefore, the whole process of spray atomization is of fundamental significance. During past decades many experimental and theoretical studies in this field have been carried out and some improved results have been obtained. Two-phase atomizers, having a variety of advantages such as spray uniformity, appreciable atomization, and smaller SMD with an increase of ambient gas, are considered to be applied in various industrial processes. The purpose of present study is to investigate the mean velocity, turbulence shear stress, turbulence intensity, mean drop size distribution, and droplet data rate in a two-phase swirling jet using PDPA systems.     

Atomization of fuel mixtures

The combustion process of a coal/oil slurry begins by atomization of the slurry. This project is a presentation of experimental system and results on atomization of coal/oil(COM) and coal/methanol mixtures with a twin-fluid and a wheel atomizer. The slurries are consisted of coal/methanol and coal/oil mixtures with two different concentrations and two coal particile sizes. The volume median diameters of the coal particles were 45 and 130 microns. The oil was No. 2 diesel oil. The droplet size was determined by photographing the spray and the photographs were analyzed to determine droplet size and distribution. The results show that the inclusion of particles in the liquid(both methanol and diesel oil) does not appreciably affect the atomized droplet size. The tendency is for the slurry droplets to be somewhat smaller than the droplets atomized with the pure liquid.     

Feature extraction of AE characteristics in offshore structure model using Hilbert-Huang transform

This paper addresses an application of recently developed signal processing tool based on the Hilbert-Huang transform (HHT) to characterize the acoustic emission (AE) signals released from the offshore structure model. The AE signals from the cracks in the welded steel nodes of the offshore structure model are collected during the tensile testing in water and the simulated AE signals are also collected in the offshore structure model. Instantaneous frequency and energy features based on local properties of the AE signals are then extracted using the Hilbert-Huang transform method. In order to demonstrate the advantage of the AE feature extraction techniques based on Hilbert-Huang transform, the conventional AE analysis is also provided side-by-side for comparison. The results verify that the method based on HHT better characterizes the AE signals than the classical AE techniques. It can be concluded that the AE signal analysis based on HHT is an effective tool to extract the features and this opens perspectives for crack recognition in offshore structures.     

Acoustic emission method for tool condition monitoring based on wavelet analysis

It is believed that the acoustic emission (AE) signals contain potentially valuable information for tool wear and breakage monitoring and detection. However, AE stress waves produced in the cutting zone are distorted by the transmission path and the measurement systems and it is difficult to obtain an effective result by these raw acoustic emission data. In this article, a technique based on AE signal wavelet analysis is proposed for tool condition monitoring. The local characterize of frequency band, which contains the main energy of AE signals, is depicted by the wavelet multi-resolution analysis, and the singularity of the signal is represented by wavelet resolution coefficient norm. The feasibility for tool condition monitoring is demonstrated by the various cutting conditions in turning experiments.     

频带能量特征法在声发射刀具磨损监测系统中的应用

基于对声发射(AE)信号特点的分析和小波包分解理论对不平稳信号特征提取的优势,提出一种利用AE信号的能量变化来监测刀具磨损状态的方法。该方法利用db8小波基对AE信号进行5层小波包分解,将分解后各频带上的能量值作为特征参数,并组成特征向量。分别提取在新刀和刀具磨损状态下的特征向量,根据其变化即可判别刀具磨损的程度。试验结果验证了该方法在刀具磨损判析中的可用性。     

燃油雾化理论研究

液体雾化在工业生产过程中应用非常普遍,雾化质量的好坏,直接影响燃油的燃烧过程.本文介绍了雾化的机理,分析了影响雾化油滴粒径的主要因素,给出了影响雾化质量的评价指标.     

On-line measurement of the size distribution of particles in a gas–solid two-phase flow through acoustic sensing and advanced signal analysis

Acoustic emission (AE) technology is a promising approach to non-intrusively measure the size distribution of particles in a pneumatic suspension. This paper presents an experimental study of the AE sensing technology coupled with signal processing algorithms for on-line particle sizing. The frequency characteristics of the AE signals under different experimental conditions are studied and compared. Initially, the characteristics of the background noise and AE signals are compared in the frequency domain for different air velocities and particle feeding rates. Through short-term energy analysis the working features of the suction unit and the vibration feeder are revealed. To find the effective characteristic frequency band of the AE signals, a multiple scanning and accumulation method assisted with a Savitzky–Golay smoothing filter is used to denoise the power spectra of the signals. Wavelet analysis is also deployed to denoise the signals. The denoising performance of different wavelet parameters (wavelet function, decomposition level and thresholding) is compared in terms of signal-to-noise ratio and signal smoothness. Finally, particle size is predicted through a neural network with energy fraction extracted through wavelet analysis. Experimental results demonstrate that the relative error of the particle sizing system is no greater than 23%.     

Performance enhancement of cryogenic machining and its effect on tool wear during turning of Al-Ticp composites

The current research is to focus on developing a liquid nitrogen diffusion system to optimize the usage of liquid nitrogen and maximizing cooling and lubrication capability by effective penetration. An atomized liquid nitrogen spray system was developed to diffuse liquid nitrogen effectively at a low flow rate (10–12 L/h) and as a high velocity (8–50 m/s) droplet jet to the machining zone. Using coated carbide tool with varying tool geometry (rake angle, approach angle, and nose radius), an investigation was performed to study the role of atomized liquid nitrogen spray-assisted machining, on performance of tool and surface quality of the machined workpiece during turning of Al-TiCp composite. To analyze the performance of liquid nitrogen spray-assisted machining, various experiments were conducted. The results obtained from the experiments reveal that the effective use of atomized liquid nitrogen spray machining is a feasible alternative to dry, wet, and cryogenically chilled argon gas. This technique significantly reduces heat generation in machining zone. The study also emphasizes the influence of tool geometry on the machinability of Al-TiCp metal matrix composites.