Visual Vibrometry and its application to NDT through the use of various video and signal processing techniques

该项目的重点是视觉振动测量领域及其通过使用各种视频和信号处理技术在超声无损检测（UNDT）中的应用。视觉振动测量的概念作为无损检测的一种方法进行了探索，利用普通消费者相机恢复信号从标准帧速率的视频。视觉振动测量技术具有很大的潜力，是无损检测中快速大面积监测的主要方法。由于视觉振动测量的工作原理是，在服务中的损坏改变振动模式的方式是不可察觉的人眼，但通过图像处理可见。NDT的一种常见形式涉及使用超声波来提取系统的底层材料和动态特性。该项目的一个目标是将超声导波的能力与视觉系统的能力联合收割机结合起来，以便穿透深度的一部分。特别是，探讨如何大面积视觉监测方法可以用来监测结构的状态。对于所收集的视频数据，利用强制激励，而不是简单地记录结构的被动响应一个目标是成功地成像结构振动的频率显着大于广告的帧速率的相机和扩展使用的相机超出其硬件规格。这可以通过利用UNDT中常见的短曝光时间和周期性激励来实现，即使激励频率超过奈奎斯特采样限制。这将涉及使用频闪效应和利用相机曝光时间，以便实现这一点，并且基本上“欺骗”相机系统以比正常可能的帧速率高得多的帧速率进行采样。这些情况下进行分析，考虑到频闪效应产生的，其中自然频率和输入激励是可计算的或已知的，分别。最后的挑战将是这些发展是否可能被推得足够远，以允许从有用的超声频率测量位移。为视觉振动测量作为一种监测和检测零件损伤的方法提供依据。为了实现这些目标的模拟和后处理工具已被开发作为一种手段，以验证实验测试和预测的实验测试的行为。其中，模拟视频旨在模仿真实的数据，并使用根据实验测试结果定义的噪声模型，以研究噪声和强度水平之间的关系，如图1所示。模拟测试视频提供了一种在物理测试之前测试实验设置的方法，并可用于探索关键摄像机参数对结果的影响。由于摄像机的动态特性对测试性能有很大影响，因此将对每个摄像机测试参数进行研究和量化。需要图像质量、帧速率和曝光时间之间的关系，并且将可能通过使用信噪比关系以及所识别的输出位移幅度和相位的精度来量化。通过使用模拟探索每个相机和测试参数的效果，可以探索测试的局限性。例如，识别可从视频数据可靠且准确地提取的最小可能像素位移。

The project focuses on the field of visual vibrometry and its application to ultrasonic non-destructive testing (UNDT) through the use of various video and signal processing techniques. The concept of visual vibrometry as a method of NDE is explored by utilising regular consumer cameras to recover signals from standard frame-rate videos. Visual vibrometry has significant potential to be a major method for rapid large area monitoring within NDE. As visual vibrometry works on the basis that in-service damage alters vibrational modes in a way that is imperceptible to the human eye, but visible through image processing. A common form of NDT involves the use of ultrasonic sound waves to extract underlying material and dynamic properties of a system. One aim of the project is to combine the ability of ultrasonic guided waves, in order to penetrate a part at depth, with the ability of visual systems. In particular, to explore how large area visual monitoring approaches may be employed to monitor the state of structures. For the video data collected, forced excitation is utilised as opposed to simply recording the passive response of the structure One goal is to successfully image structural vibrations at frequencies significantly greater than the advertised frame-rate of the camera and extend the use of the camera beyond its hardware specification. This may be achieved by exploiting short exposure times and periodic excitation common in UNDT, even when the excitation frequency exceeds the Nyquist sampling limit. This will involve using stroboscopic effects and exploiting camera exposure times in order to achieve this and essentially 'cheat' the camera system in to sampling at a significantly higher frame-rate than normally possibly. These cases are intended to be analysed by taking into account stroboscopic effects produced, where natural frequencies and input excitations are either calculable or known, respectively. The final challenge will be whether these developments may be pushed far enough to allow the measurement of displacement from useful ultrasonic frequency. In order to provide the basis for visual vibrometry as a method to monitor and detect damage in parts. To achieve these goals a simulation and post processing tool has been developed as a means to validate experimental testing and to predict the behaviour of experimental testing. Where, the simulated video was designed to imitate real data and used a noise model defined on results from experimental testing performed to investigate the relationship between noise and intensity levels as shown in figure 1. The simulated test video provides a means to test experimental set ups prior to physical testing and may be used to explore the effects of key camera parameters on the results. As the dynamics of the camera are highly influential on the performance of the testing, each of the camera testing parameters will be investigated and quantified. A relationship between image quality, frame-rate and exposure time is required and will likely be quantified by using a signal to noise ratio relationship as well as the accuracy of the identified output displacement amplitude and phase. By exploring the effect of each camera and test parameter using the simulation, the limitations of the testing may be explored. Such as, identifying the smallest possible pixel displacement that may be reliably and accurately extracted from video data.