ABSTRACT. The bridge from classical physics to quantistic physics the frontier versus new achievement in material science and non destructive testing

ABSTRACT. Coatings often prevent corrosion, extending the life of ships or offshore structures and preventing accidents. Their reliability depends on maintenance, and the key to this maintenance is the application of reliable diagnostic technology. The application of NDT technology in the field requires overcoming challenges such as the adhesion of coatings, inaccessible marine environments, and the high damping properties of the material itself. This presentation introduces the state of the art technology for measuring the thickness of coatings and evaluating adhesion. The evaluation of the coating layer was performed using an ultrasonic pulse-echo technique. A delay wire or an immersion method was used. The spectrogram of the time domain waveform of the reflected echo was analyzed. And the feasibility of guided wave technology was verified to evaluate the bonding state of the broadband coating layer. It will evolve into tomography technology for coating layers in the future.

ABSTRACT. Digital X-ray and Phased Array Ultrasound imaging inspection technologies have been well documented in the field of industrial and medical applications. The use of digital X-ray imaging has been further enhanced by techniques such as Computed Tomography (CT) that have the capability to expand the conventional 2D imaging modalities into 3D volumetric imaging. Similarly, the Phased Array Ultrasonic Imaging technology (PAUT), particularly with the FMC/TFM mode, has vastly improved the ability to image, characterize, and size defects. The ability of the advanced NDE imaging technology has reached very significant maturity permitting the operator to provide advanced insights into the state of the component, and more importantly, into the root cause analysis of the anomaly formations during manufacturing as well as prediction of the effect of these anomalies on performance of the components. While these advancements do represent a significant enhancement of diagnostic capabilities, the trade-off has been the large volume of data and the time consumed for processing this data set as well as the analysis of the processed data. This trade-off has led to requirement of additional well-trained manpower, faster processing instruments, and consequently its implementation in a post processing mode rather than the preferred in-line diagnostic mode. The presentation will highlight a new paradigm using simulation-based analysis that employs physics-based models that use parallel processing using GPU for rapid generation of synthetic data sets. This paper discusses the simulation assisted approach based on physics-based models of the different NDE/NDT imaging modalities for the development of a simulation assisted ADR (Automatic Defect Recognition) algorithm that is based on Deep Learning (DL) and/or Machine Learning (ML) mode. The approach addresses the classic issues during the implementation of DL/ML approach to industrial applications, such as Radiography and Ultrasonics based NDE/NDT data interpretation, that includes lack of sufficient apriori data as well as biases in the data sets, among others. Here, using the limited experimental/field NDE/NDT data sets that are available and by deriving critical statistical distribution parameters from this data set, the stochastics of the simulation models are determined. Thereby, the simulated data sets are generated using the numerical simulations along with the variations in the different parameters during experimental/field data acquisition. This process allows the generation of simulated data sets in large quantity that augments the smaller data sets obtained experimentally. This rich data set is subsequently utilized to train the DL models and provide reliable ADR algorithms.

ABSTRACT. Consumables for magnetic particle and penetrant testing have different potential hazards for personnel and the environment. However, safety data sheets and information on the package labels make this transparent even for users without any basic knowledge of chemistry. The official hazard ratings are becoming more and more strict as a result of new findings about raw materials.

The manufacturer can only achieve an unchanged or even improved product classification through high development efforts and substitution of ingredients. The issues of raw material availability leads to a further increase in complexity.

What should be taken into account when using the products and what developments can be expected in the future?

ABSTRACT. The fourth Industrial revolution is slowly changing the way we collect, filter, analyse and use data in inspections. NDT 4.0, a term widely used today point steadily towards the endless possibilities Internet of thing(IOT), Artificial Intelligence and robotics have enabled. Digitalisation too seems to be an important step in the establishment of NDT 4.0 as the quality and accurate labelling of data is paramount. This paper presents results on the development of a modular robotic crawler by Masterscan Engineering that is designed to be a building block on which multiple NDT techniques can be integrated with. While it explores functions of increasing accessibility, standardisation of data and IOT, it also addresses how it does not replace but aids inspectors.

ABSTRACT. While the usage of Drones for Visual, Thermography and Ultrasonic Inspections have increasingly become rampant and proven its value, 3D modelling with drones has been more catered to Construction sites, Vegetation and Urban Architecture. 3D Mapping and Modelling essentially means capture of data through either pictures or laser point cloud data and then, processing it into a 3D Model of high fidelity. This allows useful use-cases on the base level such as Ergonomics study, measurements for planning and volume calculations. However, by applying the concept of 3D modelling to process and storage Oil and Gas Plants, the same can be applied apply.

Additionally, more useful applications like updating of P&ID drawings, inspection planning and workflow optimisation can be achieved. Furthermore, as we go into further phases of Plant digitalisation – Phase 2 : CAD modelling/360 degree virtual view cam and intricate asset tagging and phase 3 : Creating a Digital Twin with uploaded inspection data base, many other useful applications can be attained. Some of those are, predictive and efficient maintenance, Site repair/erection work simulation and digitally monitoring the health of the assets. Such applications truly embody the purpose of a Digital 4.0 industry. By partnering with Advario Asia Pacific on a 3d modelling project, Masterscan Engineering and Hoversurv Technologies have completed phase 1 of the ‘Digital Twinning’ of the plant. This paper presents the workflow and use-cases attained. Lastly, it details how phase 2 and 3 can be achieved with its respective applications.

ABSTRACT. Billions of dollars are spent each year on clean, renewable energy and the operations of traditional power plants to meet the demands of electricity consumption here in the U.S. and around the world. Energy companies are always feeling the pressure to provide the electricity people rely on every day in their personal and professional lives. With bigger, more powerful computers, and the fast development of new technology, the demand for electricity will continue to grow forcing energy companies to adopt more efficient inspection applications to provide high quality, sustainable power in the future. The U.S. generated 4.12 trillion kilowatt hours of electricity in 2020. The leader in electric generation is natural gas with 40 percent of the total amount. Natural gas was followed by nuclear at 20 percent, coal at 19 percent, wind at 8.4 percent, hydro at 7.3 percent, and solar at 2.3 percent.

The NDT industry along with engineering and materials science is a critical part of the longevity of new and aging power plants around the world. This paper will discuss through examples and case studies the technology and analysis that goes into power plant condition assessments. Emphasis will be given to the NDT 4.0 technologies used in power plants to overcome traditional challenges when dealing with condition assessment inspections. It will be show that no one technology can be the answer to all problems, but that it takes a team of engineers and NDT personnel to provide high quality assessments that provide meaningful results. We will also show how Internet of Things (IoT), Augmented Reality (AR), Artificial Intelligence (AI), Machine Learning and smart technologies combined with engineering analysis and materials science can create long lived, safe, and efficient power across many different power plant types.

ABSTRACT. Diagnostics is service provided for failure prediction and anomalies detection of Industrial Equipment.

The focus is on Sound Analytics using Artificial Intelligence (AI)/ Machine Learning (ML) for failure prediction of electrical engines & motors before it happens. The Sound is the data.

The prediction of electrical engines helps the plants to reduce cost in repair and timely maintenance.

How Diagnostics works:

- Record the sound how equipment works using mobile phone and transmit data via cloud. - Process it in the cloud infrastructure for data computing, analytics, data science. - Use large dataset of different sound of industrial equipment to easily train and retrain. - Receive motor status in seconds and analyze spectrogram via UI for administrator and analysis.

The Advantages are:

- No need to install additional vibro- or noise- sensors for each electrical engine. Data is the sound. - The maintenance team on the field can record and send data for analytics to the cloud. Do not have to send inspector to site. - Knowledge solution is built-in. No need to teach new engineers how to hear if the equipment works in normal or pre-failure mode.

During tests accuracy of the models in certain cases - 93% and above.

Application Industries - Oil & Gas, Mining, Power Generation, Poultry/ Feed production, etc.

ABSTRACT. Nondestructive Evaluation, NDE, or sometimes known as Nondestructive Examination, is a process of using non-invasive methods to inspect the condition of a material or to measure the characteristics of a defect. In the modern era, technology has become a key factor in developing a world with many positive advancements. We are in the midst of a significant transformation with the aid of digitization of manufacturing; towards Industry 4.0. NDE and associated inspection technologies are key enablers of Industry 4.0. The utilization of real-time inspection data can be applied to optimize manufacturing and maintenance processes in factories to improve productivity and reduce scrap. Despite the large potential benefits, the implementation of advanced NDE technologies for these aims is relatively limited. In this presentation, it will be demonstrated how a step-by-step approach can be taken for companies looking to realize their Industry 4.0 goals using NDE. In this manner, incremental benefits can be achieved rapidly, whilst lowering implementation risk. The demonstration will be done using a series of real-life case studies. These include the optimization of ultrasonic thickness measurements in a manufacturing process. Immediate benefits can be captured by simple digitalization of thickness data and integration into existing industrial control systems. Full automation of thickness measurements utilizing robotics can then be adopted to further improve productivity and enhance repeatability. In an equivalent manner, it will be shown how the real-time digitalization of x-ray fluorescence (XRF) data can optimize metal manufacturing by controlling smelting parameters. Adaptive robotic XRF can then be used to remove operators from potentially hazardous environments whilst increasing efficiency. Step-by-step adoption of NDE technologies can produce valuable results immediately, whilst industry progresses along the journey to NDE 4.0.

ABSTRACT. Regular inspection on the condition of civil structure is critical to ensure structural integrity, prevent catastrophic failure and minimize downtime for emergency repair. Hitherto, the inspection on the anchor bolts relies on visual observation, which does not provide sufficient information to distinguish between normal and defective bolts. This paper aims to explore the classification of different types of defective anchor bolts based on ultrasonic signal through discrete wavelet transform (DWT). Multiple features are extracted from the ultrasonic signal to identify defective anchor bolts, thus improving the reliability of the inspection process.

ABSTRACT. This paper aims to study the design and fabrication of a novel ultrasonic testing probe holder for inspecting different types of carbon steel anchor bolts in an overhead position. There are many factors impacted by the new design of the probe holder, including test results quality, operating cost, inspection time, test efficiency, and inspection safety. The test consistency and time saved to inspect overhead bolts are the most important benefits for the new probe design, as it can obtain high-quality inspection results almost immediately with minimum manual operation required.

ABSTRACT. Destructive micrograph analysis (MA) is the standard method for the assessment of clinched joints. However, during the joint preparation for the MA, geometric features of the joint can change due to elastic effects and closing cracks. X-ray computed tomography (CT) is a promising alternative to investigate the joint non-estructively. However, if the material properties of similar joining partners are the same, the CT is not able to correctly resolve surfaces in the joint that are close to or pressing onto each other. These surfaces are relevant for the determination of characteristic dimensions such as neck thickness and undercut. By placing a thin, highly radiopaque tin layer between the joining partners, the interfacial area in the reconstructed volume can be highlighted. In this work, a method for the localisation of the tin layer inside the joint as well as threshold value procedures for the outer joint contour in cross section images are investigated. The measured characteristic dimensions are compared with measured values from MA of the same samples and of samples without tin layer. In addition, possible effects of the tin layer on the joining point characteristics as well as problems of the MA are discussed.

ABSTRACT. Image reconstruction by projections is basically a mathematical problem. The speed and accuracy of the reconstruction mainly depend upon, (1) discretization scheme (2) solution technique. Solution by Algebraic Method (AM) is the most promising technique for manufacturing the low-cost (few detectors arrangement) X-ray CT set-up. Slow converging rate and huge memory requirement are the two major drawbacks of the AM algorithms. Projection coefficient calculations and their storages are major time and storage-consuming processes of the algebraic methods. Among all algebraic methods, the Multiplicative Algebraic Reconstruction Technique (MART) is more effective because it maximizes the entropy of the image space. The conventional MART algorithm uses square grids (SG) in the discretization process of the image reconstruction. In the present work, we employed a modified polar grid to cope with the shortcomings of the MART method. In this new discretization scheme, only the projection coefficients of the first view, need to be calculated. Projection coefficients for other views can be easily calculated by using the symmetries of the modified polar grid. This method significantly reduces the reconstruction time and storage requirement of the MART algorithm. In addition, we also presented the direct method of polar to square grid transformation for the visualization of the reconstructed images. We tested the proposed method to fan-beam geometry for 2D image reconstruction. Structural similarity index(SSIM) and L2 error are used for quality assessment of the reconstructed images.

ABSTRACT. The fourth industrial revolution has brought many benefits to the mechanical engineering world. Through data revolution, defect segmentation in complex XCT images can now be automated in a shorter time, while achieving more accurate results. Prior work[1] proves that a deep learning approach can extract pore from every voxel of a 3D XCT data, and calculate its porosity with a high accuracy. However, it was established that training a deep learning model with limited data can cause the model to overfit, or have inferior segmentation performance than models that are trained with a larger dataset. This is a common issue in all sorts of data-driven inspection. Oftentimes, obtaining raw data and annotating these raw data for machine learning inspection can take significant resources, shifting the focus away from the network design and training.

We present XCTPore, an open source database of X-ray CT images, containing 2D slices and 3D volumetric data of X-ray CT scanned additively manufactured components, with varying porosity and image quality. This database is currently maintained by the Advanced Remanufacturing and Technology Centre(ARTC) and is open to contributions from industry practitioners, and academics. The content of the database can be queried through our python code found in our GitHub link. This database also comes with an open-source implementation of unsupervised porosity labelling function in a bid to automatically label pores without the need for human intervention. This unsupervised labelling is done using STEGO, to aid developers to label the images, to explore novel approaches.

ABSTRACT. X-RIS has developed a real-time inspection technique to quantify wall thickness variations in industrial pipes. As x/gamma rays pass through the pipe, they are attenuated according to the physical law of Beer-Lambert, modeled in Maestro software. Once the calibration has been performed on known thicknesses of a target, the raw data acquired by the digital detector makes it possible to define the corresponding thicknesses and to quantify the variations. The corrosion of the piping is thus quickly measured with user friendly tools in the Maestro software.

ABSTRACT. Owing mainly to its focusing abilities, the total focusing method (TFM) has gained popularity in the past few years for challenging applications such as small defects. Now, with the recent introduction of phase coherence imaging (PCI), new challenging applications are being used to test the extent of its benefits. In the past year, PCI has shown to improve imaging in difficult use cases including coarse-grained material, thick material, and small defects, enabling more consistent sizing than standard TFM. Although TFM enables easier image interpretation than the conventional phased array (PA) inspection technique, the use of a single element in transmission during acquisition can result in images with a low signal-to-noise ratio (SNR). This low SNR is due to poor acoustic penetration, typically in thick parts or in highly attenuative material. The PCI algorithm uses only the phase-related information of the acquired full matrix capture (FMC) signals. Removing the amplitude information from the signals enables the generation of images based solely on signal coherence. This enables the detection of flaws with signal amplitudes similar to the incoherent noise in amplitude-based TFM images. As material attenuation does not affect the phase of the signal, phase coherence TFM has proven to be especially helpful for thick or highly attenuative material inspections, such as creep damage in a thick component and fatigue crack detection on bolts and rods. Another benefit of this phase summation type of imaging is that the coherence level of the noise can be statistically defined, enabling easier dissociation of meaningful indications from noise in coarse and noisy material. The defined noise coherence threshold acts as a logical filter in generated images, separating the noise regions from the meaningful indication regions demonstrated, as is demonstrated in this paper on high-temperature hydrogen attack (HTHA) damage as well as stainless steel inspection.

ABSTRACT. HTHA (High Temperature Hydrogen Attack) damage mechanism has been heavily. under the microscope in the past years. Many new inspection techniques, as well as former more familiar techniques are now being used in conjunction to ensure detectability for this intergranular damage. The present paper offers a new approach to HTHA inspection in times where access to the component is physically limited to one side of the weld only. This challenging scenario is common in the field as components are often welded to a flange or a fitting which prevents from putting a Ultrasonic probe on each side of the weld. This new inspection strategy allowed for more energy penetrating the component as well as a reduced surface noise and was also found to be overall less noisy than other methods like TFM and conventional PAUT.

ABSTRACT. Porous materials exist widely and play an essential role in many industries and in daily life. Industrial areas where they can be easily found are energy management, vibration suppression, thermal insulation, fluid filtration, and sound absorption. The introduction of pores in a material makes it possible to modify the properties of the initial material. These changes generate or reinforce desired properties, which are not observed or exhibited in a limited way in the original material. In particular, the variation of the structural properties of porous materials, such as the porosity and the size of the pores, imply an evolution of the acoustic properties like the acoustic impedance and the acoustic attenuation of these materials. This fact explains why porous materials currently attract a huge attention in the development in the acoustic field to absorb sound noises at low frequencies of the range 2 – 6 kHz and to apply to high frequency domain. In this context, porous metals are relatively new classes of engineering materials. Research is set up to carry out studies on the ultrasonic characterization and the simulation of the porous metals in the interest of high frequency applications. Two important acoustics properties of the materials were determined from measurements in water using two methods: the first is based on an insertion-substitution technique and the second is based on a multiple reflection echoes technique. In both cases, the transit time measurements and the frequency analysis are carried out considering the reflection and transmission coefficients at the interfaces to determine the ultrasonic celerity and the attenuation in the porous material. A simulation model is developed in parallel to evaluate these results. Several porous materials were investigated with the porosity ranging from 25% to 50% with pore size ranging from 1.7μm to 60μm. The acoustic impedance of the porous material depends linearly on the porosity and can be described by a simple model of homogenization of a fluid in a solid matrix. Results show that the acoustic attenuation strongly depends on the porosity and can reach 4.3 dB.mm-1 at 1MHz.

ABSTRACT. Digital laminography is one of the Non-Destructive Testing (NDT) techniques useful for flat object inspection. The technique combines X-ray, digital detector array (DDA), and mechanical gantry and potentially be used in various engineering inspections, including components or structures made of composite. Composite material is vastly used in many engineering applications, including aerospace, automotive, and energy production. Physical defects in these engineering applications are detrimental and cause catastrophic incidents, if there are any. The unique composite internal structures often challenge NDT to be performed. This paper highlights a preliminary study on depth measurement of visible defects using digital laminography. This paper highlights the technique development and challenges of measuring the defect depth.