OPCM AE传感器特性的理论仿真与实验研究

基于均匀场和细观力学理论,对应用于结构损伤声发射(AE)检测的1-1型压电复合材料(OPCM)AE传感器,建立了它的等效力电模型,在此基础上,推出了其等效力、电参数,通过这些参数的对比,发现OPCM具有明显的正交异性的特性;同时,应用有限元仿真计算,得到了在x和z两方向上传感器受到单向应力波荷载作用时,电极面输出的电压存在明显差异;所设计的实验表明:OPCM能够区分出不同方向的应力波,并对特殊方向上的应力波具有强烈的响应,再次证实了OPCM传感器的正交异性特性。     

砂轮磨损状态的声发射检测及其误差补偿方法的研究

砂轮磨损会破坏砂轮型面，对加工精度有重要影响。利用声发射方法检测砂轮的磨损状态以及修整过程，并提出了实现砂轮磨损误差在线补偿的方法。     

Microstructural modification and mechanical property improvement in friction stir zone of thixo-molded AE42 Mg alloy

Thixo-molded AE42 Mg alloy was friction stir welded, and the soundness of joints was evaluated, together with the microstructure evolution and mechanical properties in friction stir zones. According to X-ray radiography, the optimum FSW condition range of AE42 alloy exists between AZ61 and AZ31 alloys, and it seems that the optimum welding condition range increases with decreasing Al content in the Mg alloys. There are mainly two kinds of compounds in the thixo-molded AE42 alloy, and FSW has little influence on the grainy Al₁₀RE₂Mn₇ compound, but it has great influence on Al₁₁RE₃ phase, which is changed from lamellar eutectic to small particles after welding. Furthermore, the average diameter of Al₁₁RE₃ particles in SZ decreases with increasing the traveling speed at constant rotation speed due to less heat input. The hardness in SZ is higher than that in BM, and tensile strength and elongation are both improved after welding because the stirring refines and uniforms the microstructure and intermetallic compounds.     

模具钢硬铣削过程振动和声发射信号监测与分析

硬切削作为绿色切削的重要组成部分,已成为金属切削的一个研究热点。为了对硬切削过程进行监测,建立了一套信号采集系统,通过该系统采集模具钢铣削过程中的振动信号和声发射信号,并从时域、频域对其进行了分析研究。研究结果表明：模具钢硬铣削过程的振动信号和声发射信号的时域波形呈现不同的特点;振动信号和声发射信号的均方根值随切削速度的增大均呈明显的增大趋势,而受每齿进给量和铣削深度影响很小;随着切削速度的提高,振动信号各频段的幅值均增大,但频谱分布基本不变;随切削速度的提高,声发射信号的频谱成分增多,并导致了均方根值的增大。     

急倾斜坚硬岩柱动态破裂“声–热”演化特征试验

急倾斜坚硬岩柱稳定性预测对科学采矿具有重要意义。以乌鲁木齐矿区急倾斜特厚煤层安全开采为背景,基于平面组合加载试验平台,构建急倾斜坚硬岩柱动态破裂"声–热"演化特征模型试验,采用岩石破裂声发射和红外热像综合监测方法,揭示开采扰动作用下岩柱破裂过程中的声发射与温度演化规律。研究表明:坚硬岩柱破裂过程中红外热像呈现温度辐射区(可分为低温边界区、中温过渡区和高温中心区);岩柱破裂经历弹性变形、微破裂至破裂失稳过程,该过程中温度辐射区温度逐渐降低,AE能率呈持续性增长;动态破裂"声–热"演化实质为热弹效应和摩擦热效应。这对急倾斜特厚煤层安全开采具有科学意义。     

浸水时间对饱水岩石损伤破坏过程中声发射特征影响的试验

为研究不同浸水时间饱水岩石损伤破坏过程中的力学特性和声发射特征,对天然及不同浸水时间的饱水闪长岩进行单轴压缩力学试验和声发射试验,研究单轴应力状态下其力学特性和声发射特征,结合累积声发射数与损伤变量一致的观点,建立了基于浸水时间的饱水岩石声发射损伤模型。结果表明:饱水岩石的单轴抗压强度和弹性模量随浸水时间的增加呈指数的变化规律逐渐减小,浸水60 d后其值均趋于稳定;在加载的各个阶段不同浸水时间的饱水岩样均有声发射事件产生,声发射事件率与岩样的应力-应变关系趋势均具有较好的一致性;声发射累积数的变化规律与岩样内部损伤演化规律具有一致性。     

电解质中Al2O3浓度特性的研究

针对电解槽生产过程中的ＡＩ２Ｏ３表现出来的一些特性结合模糊控制技术进行有关研究，其中主要包括ＡＩ２Ｏ３浓度与槽表观电阻关系，ＡＩ２Ｏ３浓度与电流效率关系，ＡＩ２Ｏ３浓度与ＡＥ关系等研究。这些关系及其影响因素的研究为电解槽模糊控制技术打下了基础。     

FLAC/PFC coupled numerical simulation of AE in large-scale underground excavations

Acoustic emission (AE) and microseismic (MS) events are indicators of rock fracturing or damage as the rock is brought to failure at high stress. By capturing the AE/MS events, underground excavation induced rock mass degradation or damage can be located and evaluated. A better understanding of the extent and shape of the excavation damaged zone (EDZ) or yield zone around caverns helps to arrive at safe and economic design and construction of the caverns. For this purpose, one needs to understand the AE mechanism associated with the excavation process.In the present study, a coupled numerical method is used to study AE at the Kannagawa underground powerhouse cavern in Japan. Two codes, Fast Lagrangian Analysis of Continua (FLAC), a finite difference code and Particle Flow Code (PFC), a distinct element code, are coupled. The motive to apply the FLAC/PFC coupled approach is to take advantage of each modeling scheme while at the same time minimizing the requirement for computational resources. The coupling is realized through an exchange of displacements, velocities, and forces in each cycling step. The rock mass surrounding an AE sensor is modeled using PFC and the remaining rock mass is modeled with FLAC to consider the geological complexity and the excavation sequence. In this manner, the AE activities at AE sensor locations of the Kannagawa cavern were simulated and found to be in good agreement with field monitoring results. This approach takes account of stress redistribution and provides stress and displacement patterns in the rock mass that are consistent with AE observations for excavation design. The observed AE activities in the rock mass can thus be utilized to assess the effectiveness of the rock support system and the overall stability of the cavern.     

Some Applications of Acoustic Emission in Particle Science and Technology

Acoustic emission (AE) has been used in many applications in the field of particle science and technology. AE sensors have been used in particle concentration measurements both in gas-continuous and oil-continuous flows in the oil and gas industry. To avoid formation sand flowing into pipelines, leading to erosion of valves and in many cases even to complete blockage of the flow of oil and gas, AE sensors are almost exclusively used in sand monitoring and control. These are very often among standard sensors stipulated by the operators of oil and gas production facilities in offshore, on shore, and subsea applications. Special types of sensor design have led to easy mounting of these AE sensors, which are very often clamp-on devices. This article presents a brief overview of AE-based particle monitoring in general and focuses on flange-mounted sensors in the monitoring of particle flow. By using two or more AE sensors located suitably in the process line, the particle velocity can also be evaluated, as is shown in examples using correlation in this article. The AE sensors can easily be adapted to detect malfunctioning of the process line, whether pneumatic lines or silos, just by analyzing the time series of signals from strategically based AE sensors along the process lines. Some examples are given based on recent measurement data. Finally, the article presents an overview of possibilities for improved particle flow monitoring using a multisensor suite incorporating AE sensors with other sensors/detectors such as those derived from capacitance, resistance, gamma ray, microwave, and optical devices. Artificial intelligence (AI) techniques, such as fuzzy logic and neural network algorithms, used in handling the data from these sensors lead to faster and more reliable control. Some of these topics are addressed also.     

界面剪切强度的AE监测及统计模型评估

本文成功地运用声发射(AE)技术测得玻璃丝单纤维复合材料(SFC)试验的临界断裂长度,并运用统计分析方法建立了韦伯分布纤维强度的修正界面剪切强度评估模型.本模型的计算结果与D.Jaques和J.P.Favre等模型作了比较,表明该模型描述界面剪切强度是比较切合实际的.