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Humans have an immediate perception of shapes and surroundings through their senses and their cognitive capabilities. This innate ability enables the manual inspection of components in manufacturing environments. Trained inspectors combine their senses and handling skills with bespoke non-destructive testing instrumentation. However, manual inspections can be slow for large and/or complex geometries and prone to human factors. Automated non-destructive testing systems have emerged in recent years, to increase data acquisition speed, part coverage and inspection reliability. These tools work well when the robotic inspection takes place in a well-structured environment and an accurate part model is available. However, precisely registering the position of a part in the robot reference system makes the inspection setup very time-consuming. Furthermore, the geometry of a part may differ from its digital model, spoiling the inspection accuracy. This work introduces a new approach that mimics the human perception capability and gives full manipulation autonomy to robotic sensing applications. We use a single robotized sensor to introduce a fully autonomous single-pass geometric and volumetric inspection of complex parts. Our approach can be used to solve some key challenges in quality assurance for Industry 4.0 and can find applicability beyond robotic non-destructive testing.

Robotic sensing is used in many sectors to improve the inspection of large and/or complex parts, enhancing data acquisition speed, part coverage and inspection reliability. Several automated or semi-automated solutions have been proposed to enable the automated deployment of specific types of sensors. The trajectory to be followed by a robotic manipulator is typically obtained through the offline programmed tool paths for the inspection of a part. This method is acceptable for a part with known geometry in a well-structured and controlled environment. The part undergoing assessment needs to be precisely registered with respect to the robot reference system. It implies the need for a setup preparation phase for each new part, which can be very laborious and reliant on the human experience. This work combines real-time robot control and live sensor data to confer full autonomy to robotic sensing applications. It presents a novel framework that enables fully autonomous single-pass geometric and volumetric inspection of complex parts using one single robotised sensor. A practical and robust robot control sequence allows the autonomous correction of the sensor orientation and position to maximise the sensor signal amplitude. It is accompanied by an autonomous in-process path planning method, capable of keeping the inspection resolution uniform throughout the full extension of the free-form parts. Last but not least, a by-product of the framework is the progressive construction of the digital model of the part surface throughout the inspection process. The introduced framework is scalable and applicable to widely different fields.

Nondestructive testing methods used for the testing of rail in tracks worldwide can be limited by discontinuity location or orientation within the rail. Vertical split head and rail base cracks are among those types of discontinuities that are difficult to detect, which in some cases may result in a reail failure in service. A noncontact and remote hybrid ultrasonic technique has been developed by combining laser generation with air coupled detection of ultrasonic signals in rails. The test apparatus mounts on a railroad pushcart and tests are performed in motion with all components kept above the running surface of the rail track. Tracks have been tested for vertical split head and rail base cracks with high success in detection.

Ultrasonic methods are well known as powerful and reliable tool for defect detection. Conventional ultrasonic techniques rely generally on piezoelectric transducers where transmission of energy to the material is achieved with contact. In the last decades focus and interest have been directed to non-contact sensors and methods, showing many advantages over contact techniques where inspection depends on contact conditions (pressure, coupling medium, contact area). The growing interest is also due to the further development of air-coupled probes, thanks to new materials for acoustic devices and manufacturing technologies. The use of laser as tool for ultrasonic defect detection is also an emerging approach in the industry and holds substantial promise as inspection is remote, feasible in hostile environment, can be automated and also performed with the test object in motion. Moreover, thanks to its ability of producing frequencies in the MHz range, laser-generated ultrasound enables fine spatial resolution of defects. The non-contact hybrid ultrasonic method described here is of interest for many applications, requiring periodic in service inspection or after manufacturing. Despite the potential impact of laser-generated ultrasound in many areas of industry, robust tools for studying the phenomenon are lacking and thus limit the design and optimization of non-destructive testing and evaluation techniques. Ultrasonic waves propagate through the structure interacting with defects, corners and curved surfaces, causing reflection and mode conversion. Moreover, interference between waves can produce a more complex pattern. This makes the laser-generated ultrasound propagation in complex structures an intricate phenomenon extremely hard to analyze. Only simple geometries can be studied analytically. Numerical techniques found in literature have proved to be limited in their applicability by the frequencies in the MHz range and very short wavelengths. The acoustic field in complex structures should be well understood for each application to optimize sensitivity toward a particular type of defect. A specific numerical method is presented in this chapter to efficiently and accurately solve ultrasound wave propagation problems with frequencies in the MHz range traveling in relatively large bodies and through air. Tests simulated with numerical analysis are replicated experimentally for validation. The numerical technique provides a valuable tool for studying the laser-generated ultrasound propagation and for designing and optimizing non-destructive testing and evaluation techniques. The information that can be acquired can be very valuable for choosing the right setup and configuration when performing non-contact hybrid ultrasonic inspection.

The capabilities of most non-destructive testing methods have been combined with some degree of automation in recent years, to enhance data acquisition speed, part coverage and inspection reliability. A plethora of automated or semi-automated inspection systems have been engineered to enable the robotic manipulation of specific types of sensors. Robotic inspection systems are usually operated through off-line programmed tool-paths. This approach works well when an accurate model of the part is available and the robotic inspection takes place in a well-structured environment, where the part position is precisely registered with respect to the robot reference system. However, it makes the inspection setup for each new part very time-consuming and dependent on the skills and experience of the robot programmer. Moreover, the real geometry of a part may significantly deviate from its digital counterpart, resulting in inaccurate tool paths. This work introduces a new approach capable of conferring full autonomy to robotic sensing applications, providing a breakthrough in the stateof-the-art. As a result of this work, fully autonomous single-pass geometric and volumetric inspection of complex parts, using one single robotized sensor, becomes possible. This concept can find wide applicability to the open problems of structural health monitoring of the modern age.

The spine is the load-bearing structure of human beings and may present several disorders, with low back pain the most frequent problem during human life. Signs of a spine disorder or disease vary depending on the location and type of the spine condition. Therefore, we aim to develop a probabilistic atlas of the lumbar spine segment using statistical shape modeling (SSM) and then explore the variability of spine geometry using principal component analysis (PCA). Using computed tomography (CT), the human spine was reconstructed for 24 patients with spine disorders and then the mean shape was deformed upon specific boundaries (e.g., by ±3 or ±1.5 standard deviation). Results demonstrated that principal shape modes are associated with specific morphological features of the spine segment such as Cobb’s angle, lordosis degree, spine width and height. The lumbar spine atlas here developed has evinced the potential of SSM to investigate the association between shape and morphological parameters, with the goal of developing new treatments for the management of patients with spine disorders.

Ultrasonic testing has been used for material analysis and inspection since 1930's. Nevertheless, the applicability of ultrasonic waves to new complex cases is still growing, thanks to the availability of powerful electronics and software. However, the complication that slows down the deployment of ultrasonic inspection to geometric complex parts and structures arises from the wave refraction phenomenon. A clear understanding of the ultrasound wave propagation, impacted by refractions, is crucial to interpret the data obtained from the inspection of multi-layered/multi-medium test subjects as it is not always possible to assume that mechanical waves travel in straight lines. This work presents suitable approaches for solving the ray-tracing problem in multi-layered structures. Accurate benchmarking shows that the use of the Newton-Raphson root-finding method allows a threefold reduction of the computation time, when compared to the bisection-based root-finding methods. An effective combination of the Newton-Raphson methods with bisection-type iterations is also proposed and discussed. Although the work repeatedly refers to the field of ultrasonic inspection, the presented findings are relevant and applicable to areas beyond material inspection.

The pursuit of non-contact techniques for detecting ultrasonic waves propagating on the surface of solids is stimulated by the possibility of gaining some advantages over conventional contact methods. Non-contact methods are becoming a milestone in performing non-destructive evaluation in several industrial fields, where hazardous environments, narrow spaces, high temperatures, and complex geometries are encountered. Such methods exploit photo-acoustic interactions between light and sound waves. This work compares two non-contact laser-based methods for detecting artificial flaws of different sizes in metallic specimens. It uses multi-signal homodyne interferometry and single beam deflectometry to record the ultrasonic waves produced by a piezoelectric probe capable of generating surface Rayleigh waves. The results were analysed in both time and frequency domains. Moreover, the signal-to-noise ratio was evaluated for both measurement systems by changing the distance between the defect and the point where the signals were collected. The results show the main differences between the two techniques and the practicalities associated with their usage. The employed refractometric method has a lower sensitivity to surface roughness than the interferometric method. On the other hand, the interferometric technique allows for higher spatial resolution, wider frequency bandwidth and a higher detectable frequency (i.e., detecting low-sized defects).

Finite element modelling of the lumbar spine is a challenging problem. Lower back pain is among the most common pathologies in the global populations, owing to which the patient may need to undergo surgery. The latter may differ in nature and complexity because of spinal disease and patient contraindications (i.e., aging). Today, the understanding of spinal column biomechanics may lead to better comprehension of the disease progression as well as to the development of innovative therapeutic strategies. Better insight into the spine’s biomechanics would certainly guarantee an evolution of current device-based treatments. In this setting, the computational approach appears to be a remarkable tool for simulating physiological and pathological spinal conditions, as well as for various aspects of surgery. Patient-specific computational simulations are constantly evolving, and require a number of validation and verification challenges to be overcome before they can achieve true and accurate results. The aim of the present schematic review is to provide an overview of the evolution and recent advances involved in computational finite element modelling (FEM) of spinal biomechanics and of the fundamental knowledge necessary to develop the best modeling approach in terms of trustworthiness and reliability.

Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are unavoidable differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. This could be avoided by measuring the real-geometry and the position of the specimen, which creates the paradox of having to plan robot paths for surface mapping purposes, before the originally intended robot task can be approached. Previous works have demonstrated the use of robotically manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized to the part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

In the railway field, the safety of passengers and the service life of train components are a crucial issue. For this reason, continuous periodic inspections by non-destructive techniques are required. Among these, ultrasonic tests are widely used in this field, even though the conventional ultrasound techniques have the disadvantage of requiring the disassembly of the wheels and of putting the train out of service. This procedure is expensive and time-consuming and can be neglected if non-contact ultrasonic techniques are used. In this work, the authors present an experimental research on some defects, artificially obtained on a railway wheel supplied by Trenitalia Spa, by adopting three different experimental setups and comparing the results. The proposed method uses laser equipment in generation and reception of the ultrasonic waves. The receiving unit combines a continuous wave laser and an interferometer in order to detect the surface displacements. In addition, when used in service conditions, the receiving by the interferometer is facilitated, because the tread of the wheel is very reflective (thanks to wheel – rail contact). The research aims at optimizing the experimental setup through a number of measurements carried out by varying some experimental parameters to evaluate the robustness and reliability of the technique.

Metal additive manufacturing is nowadays a well-established technology for cutting edge applications in the automotive, aerospace, defense and medical sectors. Since additive metal deposition is basically a welding method, which creates parts by successively adding layers of material, there is a chance for defects like pores, cracks, inclusions and lack of fusion to develop. As a matter of fact, interlayer and intralayer defects are often observed in additive manufactured components. However, if one considers the typical end applications along with the high costs involved in metal additive manufactured components, a “zero defect” target is close to mandatory for this technology. Planning an inclusion of the integrity assessment right into the additive manufacturing process would allow for quick corrective actions to be performed before the component is completed. Some effort has been spent in the quest of an efficient in-process flaw inspection, however, no conventional nondestructive testing (NDT) approach has been fully satisfying yet. This work suggests an experimental evaluation of the effectiveness of flying laser scanning thermography, when detecting flaws on an Additively Manufactured acetabular cup prosthesis made in titanium alloy, where some defects have been artificially created. The rough surface scanned is what’s typically left by the additive manufacturing process, and has been left so in order to prove the efficacy of the NDT inspection in real conditions. Potential benefits and limitations of the technique are discussed.