氧气球罐缺陷的声发射和磁记忆在线综合检测

采用声发射、磁记忆检测技术与常规无损检测技术相结合的方法对400m^3氧气球罐进行在线检验,得到了400m^3氧气球罐典型案例的检测方案和检测数据。结果表明,采用声发射、磁记忆检测、联合超声和磁粉检测可以实现氧气罐的在线检测,磁记忆榆测技术可以检测到内部非超标缺陷影响形成的应力集中,声发射技术评价缺陷的活性,常规超声检测可能存在表面缺陷漏检的情况,声发射、磁记忆检测弥补了常规无损检测方法的不足。容器加压声发射检测中不活动缺陷和活动缺陷的磁记忆信号有明显差异。     

压力管道声发射检测缺陷定位仿真及验证

从数值仿真和物理试验两种角度对压力管道声发射检测缺陷定位技术进行分析。首先推导了压力管道检测中声发射源定位的计算公式,而后使用多物理场耦合有限元分析软件COMSOL仿真模拟了声-压电的能量转换过程,最后使用声发射检测设备进行定位试验。结果表明:利用声发射技术对压力管道进行缺陷初定位,其结果准确可靠,可为压力管道的缺陷量化分析提供有力的先期基础。     

大型风洞承压壳体声发射评价的试验研究

在耐压试验期间及在役增压试验状态下,针对某大型风洞承压壳体开展了以结构完整性评价、缺陷监测和返修部位的缺陷活度监测为目的的声发射检测,得出了风洞承压壳体能够有效开展声发射检测,风洞承压壳体的耐压试验及在役状态下增压试验时的声发射检测能够有效评估结构完整性并进行实时监控的结论。     

声发射技术在焦炭塔检测中的应用

为缩短检验工期与减少保温拆除费用,应用声发射技术对大型焦炭塔进行了检测,并采用常规无损检测方法对声发射检测结果进行了复验。结果表明,声发射检测与常规无损检测方法发现的缺陷位置具有良好的对应关系,证明声发射检测方法在焦炭塔缺陷检测中的可行性和有效性,为类似大型石化设备声发射检测提供了重要参考。     

LD32-2 PSP海洋平台方形原油储罐在役检测

由于LD32-2PSP海洋平台原油储罐结构和应力的复杂性,以及储罐所处的特殊工况环境,使得其在使用过程中可能产生难以预测的缺陷。通过对LD32-2PSP海洋平台方形原油储罐的特点进行分析,设计和预制了储罐缺陷状态,分别对各种缺陷状态进行声发射试验,并分析缺陷的声发射信号特征,得到缺陷在升压和保压检测中的声发射信号数据,为声发射检测数据分析提供参考。经试验说明,声发射检测技术对于海洋平台储罐检测具有可行性。     

机械结构在役缺陷危害性的声发射定量评价方法

水力发电厂起重机械是用于起吊转子和闸门等大型零部件的关键特种设备,主要支撑部分为金属结构,一般为非标准设计,结构庞大,利用超声或射线等常规无损检测技术很难对它们进行全面有效的定期检测。探讨了利用声发射技术对其进行检测的可行性,通过对带裂纹缺陷的金属结构加载试验,采集活性缺陷发生发展的声发射信号。应用统计参数方法分析,提出评价裂纹缺陷的活度和强度的定量指标,进而定量评定出在役裂纹缺陷的危险性,为重大机械的定检和安全评价提供理论指导和试验数据。     

风力机叶片主梁材料缺陷演化研究

本文以含分层缺陷的风力机叶片主梁复合材料为研究对象,采用单轴拉伸测试实验和声发射技术对分层缺陷演化进行研究。通过对分层缺陷复合材料在单轴拉伸过程中产生的声发射信号进行小波包分解,并对分解后的各层频谱和能量分布进行分析。研究结果表明:采用小波包时频、小波包能量谱联合分析,能够有效识别加载过程中的缺陷演化状态对应的声发射信号特征。得出了不同损伤模式即纤维断裂、基体开裂和层间断裂的频率分布范围。为分析主梁材料破损全过程的力学及声发射特性提供了一条新思路。     

凯塞效应在压力容器缺陷评定中的应用

提出一种利用声发射技术判定压力容器缺陷来历的方法。通过水压试验时的声发射监测，利用凯塞效应原理对被检出缺陷是漏检原始缺陷还是使用后形成缺陷进行判定，为基于断裂力学理论的安全评定提供可靠保证。     

声发射在监测焊缝延迟裂纹上的初步应用

声发射技术是六十年代中期发展起来的。由于宇宙航行、原子能、航空等国防工业的发展,声发射技术受到广泛重视,应用领域日益扩大。当物体在外力或内应力作用下,其缺陷处因应力集中而产生塑性形变,所储存能量的一部分以应力波(弹性波)的形式释放出来而供物体发声,这种现象称为声发射。采用电子学方法,对发射出来的应力波进行接收并加以处理,进而评价缺陷发生、发展的规律和寻找缺陷位置的技术称为声发射技术。声发射技术的主要特点,是当材料在受载情况下,主动反映出材料内部伤情活动的信息。检验者可根据缺陷发射应力波的特点和诱发应力波的外界条件,不但可以了解缺陷的目前状态,而且也可以了解缺陷的形成历史和它在将来实际使用条件下将要发展与增大的趋势,从而可以估计缺陷的危险性。这是以往其他评价材料的方法所难以做到的。在焊接过程中,可用声发射技术探测焊缝金属由于热应力而产生的裂纹。对于焊后延迟裂纹的检测,更是简单和行之有效的一种方法。近年来,把声发射技术用于受载结构伴无损检验和安全监视以及断裂力学的研究中引起了工程界广泛的重视。     

大型结构承压壳体水压试验的声发射监测

针对大型结构承压壳体水压试验,参照GB／T18182--2000标准的相关要求,开展了以结构完整性评价和返修部位缺陷活度监测为目的的声发射监测。得出了声发射检测能够对大型结构承压壳体的耐压试验进行符合性评价并进行实时监控的结论。     

Characterisation of metal loss defects from magnetic flux leakage signals with discrete wavelet transform

Metal loss defects in a buried pipeline are detected by magnetic flux leakage technique. Characterisation of the defects and sentencing according to the severity is extremely important for organised maintenance of pipelines. In this paper we identify the parameters that characterise a defect and the features of magnetic flux leakage signal (MFL) that are affected by those parameters. We show that analysis of the MFL signal using wavelet transform scores over any other method of its kind and exposes the incompleteness of the other analysis techniques that have appeared in the literature, to date. A number of experiments were performed on a rotating drum test rig having defects of different shapes and sizes. The results from these experiments are presented and discussed in detail. Wavelet transform decomposition and reconstruction techniques were applied for denoising the raw data. We test the efficacy of discrete wavelet transform for denoising MFL signal and present a complete scheme of characterisation of defects from denoised MFL signal. We discuss the issue of defect classification and suggest that characterisation to specified accuracy, amounts to designing a classifier that assigns a defect into known classes whose shapes and sizes are defined a priory.     

Pulsed electromagnetic methods for defect detection and characterisation

The magnetic flux leakage (MFL) method has very good defect detection and location capabilities, but defect sizing capabilities, especially for sub-surface defect characterisation, are limited. The pulsed magnetic flux leakage (PMFL) technique has recently been introduced and shown to have great potential for automated defect sizing for surface-breaking defects using time-frequency signal processing techniques, but sizing of sub-surface defects has proved problematic. In this paper, pulsed magnetic reluctance (PMR), a new electromagnetic (EM) non-destructive evaluation (NDE) technique, is introduced and incorporated into a dual PMFL/PMR probe for the characterisation of surface and sub-surface defects in ferromagnetic materials. Experimental results from a comparison study of the two techniques using variety of defects analysed using time-frequency analysis show that the techniques offer complementary information, with PMFL providing defect location data and data for the characterisation of surface defects and PMR offering sub-surface defect characterisation capabilities. The work concludes that integration of these inspection techniques in the new pulsed EM probe can provide enhanced defect characterisation capabilities for flux leakage-based inspection systems using relatively simple time-frequency signal processing techniques.     

基于声发射多特征融合的搅拌摩擦焊缺陷监测

搅拌摩擦焊(friction stir welding, FSW)是一个多物理场耦合过程,焊接过程中声发射信号与焊接缺陷具有关联性. 基于声发射检测与多特征融合研究FSW缺陷监测方法,实时检测固态介质中的声发射信号,利用短时傅里叶变换、小波变换、梅尔频谱对声发射信号进行分析,确定焊接缺陷与声发射信号之间的相关性,最后通过concat融合方法构建多特征向量. 结果表明,FSW在预制缺陷处具有不同的声发射信号特征. 短时傅里叶、小波变换的主要频段集中在20 kHz,出现缺陷时功率分别达到?40,0.8 dB以上,梅尔频谱的主要频段集中在3.5 kHz出现缺陷时功率达到?40 dB以上. 应用多层神经网络分别建立基于单特征、多特征向量的焊接缺陷识别模型,多特征向量的焊接缺陷识别模型在数据集中的平均识别率达到97%,比基于单一特征缺陷识别模型提高18%. 研究的多特征缺陷识别模型能更准确地对焊接状态进行识别与监测.     

A feature extraction technique based on principal component analysis for pulsed Eddy current NDT

Pulsed Eddy current (PEC) is a new emerging NDT technique for sub-surface defect detection. The technique mainly uses the response peak value and arrival to detect and quantify the defects. This could suffer from noise and be not sufficient to extract more information about the defects, e.g. depth information of defects. This paper introduces the application of principal component analysis in extracting information from PEC responses. A comparative test carried out shows that the introduced technique has performed better than the conventional technique in the classification of defects.     

Observations of acoustic emission activity during gear defect diagnosis

It is widely recognised that acoustic emission (AE) is gaining ground as a non-destructive technique (NDT) for health diagnosis on rotating machinery. The source of AE is attributed to the release of stored elastic energy that manifests itself in the form of elastic waves that propagate in all directions on the surface of a material. These detectable AE waves can provide useful information about the health condition of a machine. This paper reports on part of an ongoing experimental investigation on the application of AE for gear defect diagnosis. Furthermore, the possibility of monitoring gear defects from the bearing casing is examined. It is concluded that AE offers a complimentary tool for health monitoring of gears.     

Metal defects sizing and detection under thick coating using microwave NDT

An experimental study to evaluate shapes and sizes of defect under thick coating by microwaves NDT is demonstrated. Specially fabricated thick fire protect coated steel panels with embedded defects are inspected using an X-band (8.2–12.4 GHz) open-ended rectangular waveguide. The fundamental idea behind using this probe is presented along with several experimental results to validate this method for defect detection under coating. The reflected signal related to the phase and magnitude of the reflection coefficient at the waveguide aperture is used to create images of these coated samples under test. These images indicate the ability of microwaves for identifying and sizing defects under thick coating layer. Linear sweep technique is used here to obtain multiple frequency spectrum variances. Principle Component Analysis (PCA) algorithms have been employed to enhance the resolution of our proposed method. A series of performance comparison with PCA algorithms are also provided to extract the defect features from thick coating layer influence. To evaluate the proposed technique, steel with known defect and five coated steel plates with unknown defect under different coating thickness are measured. Results indicate that the defect detection capability has been enhanced with the suitable use of signal processing methods.     

冷轧宽厚规格深冲钢梗印缺陷成因分析及其控制措施

针对山东钢铁集团日照有限公司2 030 mm冷轧产线宽厚规格深冲钢卷出现大量梗印缺陷问题,通过现场实测与多功能仪自动检测相结合检测缺陷卷热轧卷横断面轮廓曲线,检测热轧卷微观组织及硬度等方法,分析了梗印缺陷的形成原因。结果表明:带钢横断面存在连续局部高点,卷取中局部高点逐层累加形成鼓包,因深冲钢屈服强度较低,成卷后局部高点处存在应力集中,使其沿径向和横向发生延展变形而导致梗印缺陷的形成,且梗印缺陷卷开卷后在带钢边部形成浪形。为此,在热轧工序通过优化轧辊轴向横移、弯辊策略以及调整轧制节奏等措施,增大工作辊辊缝凸度,从而有效改善热轧带钢横断面局部高点缺陷,为冷轧工序提供合格原料。在冷轧工序通过优化工作辊辊缝形状、分小卷卷取等措施,宽厚规格深冲钢的局部高点可得到有效控制,显著降低了因梗印缺陷造成的不良改判率。     

用直流电位梯度法测量埋地管道防护层缺陷位置的模拟试验

介绍了埋地管道防护层缺陷电位梯度检测技术。用盐溶液、蒸馏水和自来水的混合液模拟土壤介质,通过改变管道防护层缺陷大小,改变环境电阻率和保护电流,试验证明了电位梯度检测技术能够比较准确地检测出管道防腐层缺陷的位置,并得到了管道埋深和地表电位梯度的关系。     

超声激发下缺陷红外信号的识别

超声红外热像技术是一种组合功率超声和红外热像技术的新兴无损检测技术。实现其对缺陷信号的自动识别,有利于提高该技术的检测效率。给出了超声激发下缺陷处温度场特性,以此作为识别缺陷信号的依据。通过对实际获取的缺陷红外热像的分析,说明在超声红外热像技术中通过温度场特性进行缺陷红外信号识别是可行的。