基于三点弯曲试验的聚丙烯塑料颗粒混凝土声发射分析

为探讨掺入聚丙烯(PP)塑料颗粒对混凝土疲劳损伤的影响,以不同塑料颗粒掺量Wf(0、10%和20%)混凝土为研究对象,采用声发射技术,开展一系列三点弯曲疲劳试验。试验结果表明:掺入塑料颗粒后,混凝土疲劳寿命增大,断裂能增大,但可承受的最大荷载降低,挠度增大,塑性变形能力增强;声发射定位的损伤源主要集中在跨中,首次峰值荷载前,声发射事件偏少,声发射定位可识别的内部疲劳损伤点较少,当接近疲劳破坏阶段,声发射信号源急剧增加,且随着Wf的增加,声发射事件数量明显减少,声发射事件主要出现在循环荷载波谷处;掺入塑料颗粒后,声发射信号次数显著降低,持续时间更短,且随着Wf的增加,声发射信号次数进一步降低。掺入PP塑料颗粒有助于缓解混凝土内部疲劳损伤,延长其疲劳寿命。

基于声发射参数分析的红层泥岩高周循环加卸载损伤及变形特性

为研究不同应力上限及加载频率条件下软弱红层泥岩的损伤及变形特性,基于声发射损伤监测手段开展高周循环加卸载试验,系统分析应力上限与加载频率对红层泥岩损伤及裂纹扩展模式的影响。结果表明:当应力上限低于屈服临界动应力值时,泥岩经历先剪缩后缓慢剪胀的过程,岩样中微裂隙的发展与黏土矿物的膨胀逐渐占据主导地位;低频AE信号产生于静载阶段,而高频AE信号主要出现在循环加载阶段,且随加载频率的增大,超过300 kHz的超高频声AE信号占比逐渐增大;红层泥岩循环荷载下所产生的裂纹总体以张拉裂纹为主,但第I阶段剪切裂纹占比相对其他阶段较大,且随着动应力幅值减小或加载频率的增大,剪切裂纹所占比例减小;在裂隙自愈合效应下,泥岩中由动载引起的损伤裂隙会被逐渐修复,且随着放置时间的增加,声发射Kaiser效应逐渐减小甚至消失。

岩样破裂过程声发射参数特征与时频特性分析

岩样破裂声发射信号中包含破裂关键时频信息,探究信号参数与岩样破裂前兆特征之间的关系对岩石工程灾害的预测具有现实意义。传统的伪维格纳分布(Pseudo Wigner-Ville Distribution,PWVD)算法能够通过对信号加窗来突出信号的局部特征,但是试验采集的信号一般是实值,直接运用PWVD进行时频分析可能会出现虚假频谱的情况。针对该问题,提出了一种基于Hilbert变换(Hilbert Transform,HT)的HPWVD时频分析方法对声发射信号展开时频研究。首先通过单轴压缩试验采集到钨岩、砂岩的破裂声发射信号;然后运用参数分析法对2种岩样累计振铃计数及累计能量的分布特征展开分析,并由此划分破裂阶段及确定破裂阶段临界点;最后运用HPWVD算法获取临界点前后的声发射信号的时频特征。研究结果表明,运用HPWVD算法对信号进行时频分析能够很好地消除虚假频谱的现象,并能准确获取临界点前后的时频信息,即岩样在破裂前的能量会在新的频段内重新分布与聚集,为岩样破裂预测提供了依据。

利用全信息声发射仪实现恢复系数与重力加速度的快速测量

本文利用DS2型全信息声发射信号分析仪构建了可以快速测量并计算出小球与平板之间弹性碰撞恢复系数及重力加速度的实验测量系统。通过实时记录小钢球与瓷砖地面之间,玻璃球和弹力球与钢板之间3种不同碰撞模式下的碰撞全波列,本文分析获取了相邻两次碰撞之间的时间间隔序列T_n,并建立了lnT_n与碰撞次数n之间的线性关系,从而实现对弹性碰撞恢复系数及重力加速度的快速测量与分析。实验测量表明,弹性碰撞恢复系数与重力加速度快速实验测量系统具有实验原理简单、清晰,记录的碰撞波形清晰、完整,实验测量精度高和稳定性好的特点。

123例窒息新生儿发声分析

目的 :探讨窒息新生儿用耳声发射发现听力障碍情况。方法 :对 2 0 0 1年 7月～ 2 0 0 3年 6月间在本院出生的窒息新生儿 12 3例及同期分娩的正常新生儿 5 0 2 2例采用耳声发射分析仪进行听力测试 ,在分娩后 3～ 5d ,4 2d ,90d分别进行测试 ,如 3次均未通过者则进行ABR检查 ,2次异常确诊为听力障碍。结果 :Ⅰ 窒息组出生 3～ 5d异常率为 16 83% ,Ⅱ 窒息为 4 0 91% ,正常儿为 7 0 1% ,前 2组与正常儿组比较均为P <0 0 1。出生 4 2d无复测。结果前 2组与正常组之间比较均P <0 0 1。出生 90d复测Ⅰ 窒息组与正常儿组之间比较P >0 0 5 ,而Ⅱ 窒息组与正常 2组比较P <0 0 1。ABR检查结果Ⅰ 窒息儿全部通过 ,Ⅱ 窒息儿未通过率为 9 1% ,正常儿为 0 199%P <0 0 1。结论 :重度窒息致新生儿脑部缺血缺氧可能是致新生儿听力异常的因素之一 ,使耳蜗毛细胞受损 ,蜗内电位发生改变 ,故重度窒息听力障碍发生率明显高于正常儿组 ,要求做好产前检查 ,对可能引起新生儿窒息的原因充分重视 ,加强胎儿监护 ,预防新生儿窒息发生 ,同时应做好新生儿听力筛查 ,早期发现 ,早期干预 ,以减少聋哑发生。

真三轴煤层钻孔承载破坏层理效应试验研究

为探究层理对真三轴环境下煤层钻孔动态破坏特征影响,采用煤岩体单面可视真三轴试验仪器开展含层理煤层钻孔承载破坏试验,并结合数字图像相关和声发射分析方法进行研究。研究结果表明:试样破坏经历3个阶段,阶段Ⅰ,分析区域边缘剪切应变集中,孔壁破裂伴随煤颗粒弹射,声发射累计事件数和能量活跃性较低;阶段Ⅱ,孔周剪切应变场呈蝴蝶形状分布特征,孔壁两侧煤碎片弹射、煤块剥落,呈“V”形破坏,声发射累计事件数和能量活跃性较高;阶段Ⅲ,试样层理处剪切应变集中,出现宏观剪切裂纹,呈拱形分布特征,声发射累计事件数和能量活跃性强烈。研究结果对钻孔卸压机制研究具有参考意义。

PC箱梁损伤演化声发射监测及破坏试验研究

为了研究预应力钢筋混凝土(PC)箱梁损伤演化的声发射特性,开展了PC箱梁的静力破坏试验。综合采用常规应力、应变和挠度测试技术,记录了加载过程中PC箱梁主要位置混凝土、普通纵筋和箍筋的应变情况、梁体挠度及声发射信号,以全面分析PC箱梁损伤演化过程中的声发射特性。采用声发射特征参数分析方法(包括计数-幅值、能量-平均频率和幅值-持续时间的关联分析及b值分析法),获取了该结构表面裂纹出现、弹塑性工作状态转变点和结构破坏的声发射信号特征。试验结果表明:PC箱梁试验过程以中低幅值(40~80 dB)和低频(20~80 kHz)声发射信号为主,斜截面开裂后,平均频率逐渐向较高频率转移;斜截面开裂对应的荷载阶段(355~410 kN),各幅值范围下的总计数突然呈倍数增加,声发射活性突然增强,且相对正截面开裂时声发射信号更活跃,说明斜裂纹越多释放出的声发射信号更强,且更易被识别出;临近破坏前,大于140 kHz的能量占比急剧增加,超过10%,该特征变化可作为试件破坏的前兆;幅值随持续时间的分布从分散趋于集中时预示试件进入弹塑性工作状态;b值出现极小值时预示试件出现弯曲开裂,且随荷载持续增加过程是弯剪开裂过程,b值分析法能良好地反映出PC箱梁结构损伤演化过程。

畸变产物耳声发射在精神性耳聋诊断中的应用

目的探讨畸变产物耳声发射在精神性耳聋诊断中的应用价值。方法选取2013年8月到2014年12月在我院就诊的60例精神性耳聋患者,该60例患者作为观察组,同时选取60例听力正常并且无耳鸣的正常人作为对照组,采用耳声发射分析仪对两组患者进行畸变产物耳声发射检查,并分析结果。结果对照组患者治疗前平均听阈显著低于观察组,两组相比较,差异具有统计学意义(P<0.001);治疗后观察组患者平均听阈下降;两组患者治疗前d B SPL相似,差异不具有统计学意义(P=0.58);治疗后观察组患者d B SPL与治疗前相比,差异不具有统计学意义(P=0.63),和对照组相比,差异也不具有统计学意义(P=0.56);两组患者治疗前d B n HL相似,差异不具有统计学意义(P=0.17);治疗后观察组患者d B n HL与治疗前相比,差异不具有统计学意义(P=0.85),和对照组相比,差异也不具有统计学意义(P=0.79)。结论畸变产物耳声发射检查可作为一种常规听力检查对精神性耳聋作出客观、有效、可靠的诊断。

关于新生儿听力筛查的最佳测试时间

目的:探讨对新生儿进行听力筛查的最佳时间,并对测试结果做分析和说明。方法:将新生儿按照出生天数分成几组,用美国Bio-logic公司出品的Audx耳声发射分析仪(新生儿听力筛查仪)对600名新生儿进行听力筛查。结果:结果发现出生后1、2、3、4、5天听力通过率分别为32.05%、50.76%、92.05%、94.55%、93.82%。结论:所以我们发现用Audx耳声发射分析仪进行新生儿听力筛查的最佳时间为出生3天以后。

Identification of damage mode in AZ31 magnesium alloy under tension using acoustic emission

In order to characterize different damage modes, real-time detection of the tensile cracking process for AZ31 magnesium alloy was performed using acoustic emission （AE） technique. Results showed that elastic deformation, plastic deformation, microcracking, stable and unstable propagation occurred during crack damage. Four damage modes were determined using AE multiparameter analysis. Dislocation motion signals with amplitudes 〈70 dB and twinning signals with 70-100 dB were found. Microcrack signal energy was concentrated from 2400 aJ to 4100 aJ, mainly at a rise time of less than 800 gs. A stable crack propagation signal had high peak to counts in the 20 to 50 range, whereas its ring count was in the 20 to 2000 range. The average frequency of unstable propagation signals was approximately 100 kHz, with duration from 2000 gs to 10s gs. The damage mechanisms and AE resources from different crack propagation steps were discussed. Various damage modes could be characterized by different AE signal parameters when they appeared simultaneously during crack propagation.

Feasibility analysis for monitoring fatigue crack in hydraulic turbine blades using acoustic emission technique

In order to investigate the feasibility of monitoring the fatigue cracks in turbine blades using acoustic emission (AE) technique, the AE characteristics of fatigue crack growth were studied in the laboratory. And the characteristics were compared with those of background noise received from a real hydraulic turbine unit. It is found that the AE parameters such as the energy and duration can qualitatively describe the fatigue state of the blades. The correlations of crack propagation rates and acoustic emission count rates vs stress intensity factor (SIF) range are also obtained. At the same time, for the specimens of 20SiMn under the given testing conditions, it is noted that the rise time and duration of events emitted from the fatigue process are lower than those from the background noise; amplitude range is 49-74 dB, which is lower than that of the noise (90-99 dB); frequency range of main energy of crack signals is higher than 60 kHz while that in the noise is lower than 55 kHz. Thus, it is possible to extract the useful crack signals from the noise through appropriate signal processing methods and to represent the crack status of blade materials by AE parameters. As a result, it is feasible to monitor the safety of runners using AE technique.

Application of discrete wavelet operations in the detection of acoustic emission of coal and rock rupture

Through the 5-channel SWAES digital full waveform AE detector, the paper dealt with the fracture process of coal and rock samples under uniaxial compression. Using wavelet operations of multi-scale discrete analysis the pulses of a particular time period （points） and the space domain signal by numerical method were gotten, and the paper concluded that the signal singularity in load rupture had closely relations with fracture and uniaxial compression. The detected position and the actual breaking point only differed at one sample point, the relative error was 6.82%, and there was no accumulative error. Thus it provided an effective method to solve the problem of instability analysis of the signal singularity detection and coal-rock compression failure in the whole process.

Wall sheeting diagnosis in fluidized beds based on chaos analysis of acoustic emission signals

A novel method, based on acoustic emission (AE) techniques, for detecting agglomeration in fluidized beds is presented. Particle size characteristics are determined based on the principle that AE signals with different frequency band energies are emitted when particles of different sizes impact an internal wall. By applying chaotic analysis to the AE signals, the malfunction coefficients are well defined. Agglomeration in the fluidized bed can then be detected by the sudden variation of malfunction coefficients. AE signals were investigated in a laboratory scale heated fluidized bed and an industrial polyethylene fluidized bed. Experimental data showed that the malfunction coefficients increased with the growth of agglomeration. The results indicated that agglomeration in fluidized beds can be predicted and diagnosed effectively and precisely using AE techniques based on chaotic analysis.

Fatigue damage characterization of carbon fiber reinforced polymer bridge cables:Wavelet transform analysis for clustering acoustic emission data

Carbon fiber reinforced polymer(CFRP)has many remarkable merits.It is lightweight and has great rigidity and high intensity. High-durability cable produced from CFRP as reinforcement material is widely used in bridge construction projects.However, there is a dearth of studies regarding damage types and mechanism under fatigue load of CFRP bridge cables.In this paper,we adopt acoustic emission(AE)technology to monitor fatigue damage and failure of the CFRP bridge cables,specifically by monitoring the bridge cable’s fatigue test process and using wavelet transformation to analyze data.Results show that damage on the CFRP cable is divided into three stages.Based on wavelet singularity theory,in each stage of AE,the burst signal is obtained and its time-frequency distribution is achieved through wavelet analysis.According to the analysis results,failure modes in each phase and type of acoustic emission source are easy to determine.The characteristics of waveform,types of damages, and frequency distribution of CFRP bridge cable in different damage phases are collected.Research shows that the method used to determine the types of fatigue damage on the CFRP cable is feasible according to the range of distribution characteristic parameters for acoustic emission signal and type of waveform.

Real-time damage analysis of 2D C/SiC composite based on spectral characters of acoustic emission signals using pattern recognition

In this study,unsupervised and supervised pattern recognition were implemented in combination to achieve real-time health monitoring.Unsupervised recognition(k-means++)was used to label the spectral characteristics of acoustic emission(AE)signals after completing the tensile tests at ambient temperature.Using in-plane tensile at 800 and 1000°C as implementing examples,supervised recognition(K-nearest neighbor(KNN))was used to identify damage mode in real time.According to the damage identification results,four main tensile damage modes of 2D C/SiC composites were identified:matrix cracking(122.6–201 kHz),interfacial debonding(201–294.4 kHz),interfacial sliding(20.6–122.6 kHz)and fiber breaking(294.4–1000 kHz).Additionally,the damage evolution mechanisms for the 2D C/SiC composites were analyzed based on the characteristics of AE energy accumulation curve during the in-plane tensile loading at ambient and elevated temperature with oxidation.Meanwhile,the energy of various damage modes was accurately calculated by harmonic wavelet packet and the damage degree of modes could be analyzed.The identification results show that compared with previous studies,using the AE analysis method,the method has higher sensitivity and accuracy.