声发射监测技术在磨削加工中的应用

在磨削加工中，砂轮的工作状况是不断变化的，因此，对砂轮的修整及磨削过程进行监测是非常必要的。本文将声发射信号应用到对磨削过程的监测上，通过监测砂轮修整过程可以得到一致的砂轮表面质量。通过监测ＡＥ信号的幅值和频谱特征即可确定砂轮的寿命。用ＡＥ信号可以成功地检测出砂轮和工件的初始接触时间，为砂轮向工件进给时的准确对刀及高精度表面质量的获得提供了有效的方法。     

基于LSTM和声发射的金刚石砂轮磨损状态识别

针对超精密磨床磨削加工中对砂轮磨损状态监测和识别的需求,基于长短时记忆网络(LSTM)建立砂轮磨损状态识别模型,通过小波包分析提取砂轮磨损敏感频段的特征,继而使用降维后的敏感频段频域特征为输入来训练模型以识别砂轮的磨损状态,并对比了不同超参数下的LSTM网络以及传统前馈神经网络的识别效果以获取最佳模型.完整寿命周期的金...     

超硬铸铁磨削用CBN砂轮磨钝过程的声发射检测

用声发射技术监测砂轮磨钝过程是一种方便而且可靠的新方法。在用CBN砂轮磨削超硬铸铁的基础上,研究了砂轮磨钝与声发射信号之间的关系。结果表明:(1)声发射信号的幅值能准确地反映砂轮的磨钝状态;(2)声发射信号的RMS值以及声发射计数率也同砂轮的磨钝状况相符;(3)锋利的砂轮和磨钝了的砂轮具有明显不同的功率谱。利用上述参量可以确定本试验条件下CBN砂轮的耐用度,预报和检测砂轮的磨钝及磨削烧伤。     

声发射技术在防喷器检测中的应用

简要介绍了国内声发射技术在防喷器检测的应用现状。总结了声发射技术检测的在用防喷器使用状况表,对不同型号的防喷器和使用时间不同的防喷器进行分析,统计出防喷器的使用状况规律。根据声发射的检测结果分析了防喷器的缺陷成因,为防喷器的继续使用和维修提供依据。声发射技术应用于防喷器的检测非常成功,最后提出了目前急需解决的问题和发展趋势。     

声发射技术在钢丝绳失效测试中的应用

回顾了声发射（AE）技术在钢丝绳失效测试中的应用历史。对疲劳条件下6×19S＋FC钢丝绳进行了AE测试,结果表明用参数一幅值、持续时间、能量和计数综合表征断丝可使其检测定量化,对疲劳条件下钢丝绳断丝定位问题,AE线定位技术同样适用。     

声发射技术在阀门检漏中的应用

提出采用声发射技术检测阀门的泄漏，介绍了声发射检测原理、声发射传感器的制作方式以及信号处理方式。试验和实际检测证明，采用声发射技术检测阀门的泄漏是可行的，检测简便、快捷、准确，扩大了声发射技术的应用范围，有效地监控了阀门的泄漏状况。     

JS1100大型自动控制砂轮回转试验机

本文介绍了大型自动控制砂轮回转试验机的设计研制，通过设计体式砂轮卡盘及新结构防护罩，采用交流变频、计算机控制技术，研制出了新一代性能优良的大型回转试验机，具有自动化程度离，操作维护简便，数字化显示主轴转速，节能等优点。     

cBN砂轮在低速磨削中的应用

cBN砂轮在高速设备上使用非常广泛,但在老式低速磨床上采用cBN砂轮的非常少。我们在这方面做了大胆的尝试,就是在老式磨床上不做任何改进,直接更换相同直径的陶瓷cBN砂轮,通过更换皮带轮改变传动比,把砂轮速度从51.4 m/s提升到64.8 m/s,增大冷却液流量、压力,确定冷却液冲刷位置,改变切削的进给量,使cBN砂轮的一个修整频次内寿命大幅提升。最后证明陶瓷cBN砂轮在低速磨床中一样可以替代刚玉砂轮,并且不需要大的改造投资,可以获得非常好的综合经济效益。     

Characterization of the grinding process by acoustic emission

The properties of a ground surface can be estimated on-line during manufacturing based on the analysis of acoustic signals emitted by the grinding process. This possibility is demonstrated using an experimental system comprising an external grinding machine, a data acquisition unit and an artificial neural network. In the initial phase of system application, an empirical model of the grinding process is formed in the memory of the neural network by self-organized learning driven by empirical data consisting of the acoustic emission spectrum and a surface roughness correlation function. After learning, the system applies the model to estimate the correlation function of the surface profile from the input acoustic emission spectrum. For this purpose, non-parametric regression, based on the conditional average estimator, is utilized. Experiments were done on the grinding of hardened steel workpieces by a corundum wheel. During formation of the model, the surface profile and its correlation function were determined off-line, while in testing system performance the surface correlation function was estimated on-line from the acoustic emission spectrum. With respect to the estimation error, three characteristic periods of the process were observed corresponding to grinding with a newly dressed, slightly worn, and worn out wheel. The best estimation is obtained during grinding by a slightly worn wheel.     

布料工艺对砂轮回转强度影响机理探讨

依据最大应力学说理论,分析了提高砂轮孔径处密度以增加砂轮强度的机理。在此基础上,对磨具成型压强、磨具烧后收缩、成型料与模具间的摩擦力等影响成型密度的因素进行研究,并结合生产实际得出结论。研究结果表明:（1）在一定的条件下,提高成型密度可以有效地提高砂轮的抗拉强度;（2）在布料角满足0<θ≤θ₀条件下,提高布料倾斜角θ可以有效地提高砂轮的抗拉强度。      

基于声学原理陶瓷砂轮性能表征的探讨

通过采集不同结合剂和磨料粒度的陶瓷砂轮的声学信号进行对比,试图探讨不同陶瓷砂轮声学特性上的反应。实验结果表明:随着陶瓷砂轮结合剂或粒度的改变,其声波的频幅图和相位图都会发生变化,经过快速傅里叶变换和小波变换处理后的声波的频幅图简单、特征明显。若应用大数据的处理方法,采用声波特性来对砂轮性能进行全面表征是可行的。     

Neural network detection of grinding burn from acoustic emission

An artificial neural network (ANN) approach is proposed for the detection of workpiece “burn”, the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.     

Trouble diagnosis of the grinding process by using acoustic emission signals

The focus of this study is the development of a credible diagnosis system for the grinding process. The acoustic emission signals generated during machining were analyzed to determine the relationship between grinding-related troubles and characteristics of changes in signals. Furthermore, a neural network, which has excellent ability in pattern classification, was applied to the diagnosis system. The neural network was optimized with a momentum coefficient (m), a learning rate (a), and a structure of the hidden layer in the iterative learning process. The success rates of trouble recognition were verified.     

铝基金刚石磨轮在陶瓷加工中的应用

Fe基、Cu基、Co基金刚石工具已有大量研究,Al基金刚石工具未见报道.本文采用整体烧结法制备了结合剂组成分别为Al-Sn-Ti、Al-Sn-Ti-Ni-Co、Al-Sn-Ti-Ni、Al-Sn-Ni-Co的铝基金刚石磨轮,分析了铝基金刚石磨轮磨削陶瓷后的显微组织,对比了铝基金刚石磨轮、树脂金刚石磨轮、斜齿金刚石磨轮对不同种类陶瓷砖的修整效果.结果表明:采用A1-Sn-Ti-Ni-Co作结合剂在300℃烧结制备的金刚石磨轮,金刚石出刃高,对陶瓷砖修整效果好,适用砖质广;铝基金刚石磨轮与树脂基磨轮生产成本基本相当,但使用寿命比树脂金刚石磨轮提高3倍以上.     

硬质合金PA30高速深磨过程中声发射信号特征的变化研究

在硬脆难加工材料硬质合金PA30高速深磨声发射实验中,随着工件速度和磨削切削深度增加,声发射信号特征参数均方根（AE_RMS）和磨削力变大;随着砂轮速度增大,AE_RMS和磨削力减小。磨削力和AE_RMS有相同的变化趋势。硬质合金PA30高速深磨AE频谱的能量在100~600kHz的频段比较集中,其AE信号频谱的能量与频率范围明显高于低速浅切磨削。      

磨削加工中砂轮对刀技术概述及声发射应用试验研究

介绍了磨削加工中常用的人工对刀、对刀仪对刀、阻力对刀、导电对刀、声发射对刀等各种砂轮对刀方法及其特点。针对声发射技术在对刀环节中的应用,我们进行了多种磨削条件下的砂轮对刀测试。试验结果表明:声发射测试技术可用于砂轮修整对刀、磨削对刀;声发射信号的波形、频率分布、波形参数均可反映对刀状态,但对刀信号易受磨床环境噪声条件影响;在同一磨床上,砂轮磨削对刀信噪比高于砂轮修整对刀;在不同磨床上,普通磨床上砂轮修整对刀信噪比高于数控磨床。