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Jaber, A.;  Karganroudi, S.S.;  Meiabadi, M.S.;  Aminzadeh, A.;  Ibrahim, H.;  Adda, M.;  Taheri, H. Classification of Non-Destructive Evaluation. Encyclopedia. Available online: https://encyclopedia.pub/entry/31826 (accessed on 04 September 2024).
Jaber A,  Karganroudi SS,  Meiabadi MS,  Aminzadeh A,  Ibrahim H,  Adda M, et al. Classification of Non-Destructive Evaluation. Encyclopedia. Available at: https://encyclopedia.pub/entry/31826. Accessed September 04, 2024.
Jaber, Ali, Sasan Sattarpanah Karganroudi, Mohammad Saleh Meiabadi, Ahmad Aminzadeh, Hussein Ibrahim, Mehdi Adda, Hossein Taheri. "Classification of Non-Destructive Evaluation" Encyclopedia, https://encyclopedia.pub/entry/31826 (accessed September 04, 2024).
Jaber, A.,  Karganroudi, S.S.,  Meiabadi, M.S.,  Aminzadeh, A.,  Ibrahim, H.,  Adda, M., & Taheri, H. (2022, October 28). Classification of Non-Destructive Evaluation. In Encyclopedia. https://encyclopedia.pub/entry/31826
Jaber, Ali, et al. "Classification of Non-Destructive Evaluation." Encyclopedia. Web. 28 October, 2022.
Classification of Non-Destructive Evaluation
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This entry is adapted from the peer-reviewed paper 10.3390/ma15207187

Inspection methods, also known as non-destructive evaluation (NDE), is a process for inspecting materials, products, and facilities to identify flaws, imperfections, and malfunctions without destruction or changing the integrity of materials, structures, and mechanisms.

non-destructive evaluation (NDE) artificial intelligence (AI) machine learning (ML)

1. Introduction

Overall testing, inspection, and certification services have been continuously carried forward along with INDUSTRIAL revolutions. The testing, inspection, and certification market is projected to grow from $221 billion in 2022 to $268.9 billion by 2027 [1]. Testing, inspection, and certification services help manufacturers improve productivity, meet global standards, and enhance product and service quality for any product, service, or process. Part of that has been due to testing, inspection, and maintenance developments to keep up the production and service processes and ensure infrastructure health and safety regardless of the sector in which the company operates. Of all these developments, non-destructive evaluation methods (NDE) are of great importance because of their detection and characterization capabilities. Non-destructive evaluation is a set of techniques that do not destroy materials during inspection [2]. NDE is the evaluation and analysis technique that enables inspecting materials or components without causing any damage to the part [3] in a safe and reliable manner. Moreover, NDE methods are cost-effective and safe for workers. These methods are mainly used in aerospace and manufacturing industries [3] and vary from visual inspection performed by engineers specialized in the field to chemical and liquid penetration tests, alternative current, acoustics, etc. [4].
However, the contemporary industry is struggling with new challenges that prohibit modernization and synchronization. Due to the large volume of data and innovative technologies that are emerging exponentially and in response to the need for better and faster production, the world has entered a new stage of the industrial revolution, which is also called Industry 4.0. Industry 4.0, defined as the digital transformation of the business [5], is a relatively new concept that includes the most important technological developments in the fields of automation, control and information technology applied to production processes. It incorporates concepts ranging from physical-cyber systems to the Internet of Things (IoT) and Internet services, and production processes are becoming more efficient, autonomous and adjustable [6]. Driven by a large amount of available data [7], Industry 4.0 is transforming manufacturing into smarter automation in many ways, including the installation of intelligent robots, sensors, the use of collaborative robots, and the use of manufacturing simulations [8]. An Industry 4.0 typical example is the introduction of a monitoring system that monitors equipment in real-time by the means of AI algorithms to automatically detect and identify defects [9].

2. Classification of NDE Methods

In general, NDE methods can be classified based on various factors, including the type of physical field, type of defect, and performance characteristics. In order to classify NDE methods based on physical fields, electric, magnetic, thermal, and mechanical fields can be highlighted. Defects can also be classified into surface and subsurface defects. Accuracy, efficiency, safety, and cost are the most important determinative parameters. Table 1 presents an overview of some of the NDE methods.
Table 1. An overview of the NDE methods and their advantages and disadvantages.
Methods   Visual Evaluation Eddy Current Ultrasonic Thermographic Inspection Radiographic Testing Laser 3D Scanning Laser Spot Thermography
  Criteria
Source - Eddy current Acoustic vibration Thermal emissivity X-ray/Gamma-ray Laser beam Heat distribution
Material All Conductive materials All All All All Metals
Contact requirements Non-contact Non-contact Contact/Non-contact Non-contact Non-contact Non-contact Non-contact
Advantage Easy to implement, low cost Low-cost, no surface treatment Great depth penetration, high resolution Full-field, fast, high resolution, high sensitivity High resolution Full-field, fast, high resolution High surface temperature, hazardous environments, high resolution
Disadvantage Surface defects, safety problems, time-consuming, low reliability Scanner required Sound attenuation, time-consuming, 2D measurements Scanner required, detection of false positives, limitation due to thermal properties of materials Radiation hazards, relatively slow, scanner required Surface defects Surface defects, time-consuming

2.1. Visual Evaluation (VE)

Visual evaluation is the process of collecting data visually. This type of inspection requires a team of trained and experienced inspectors and usually does not require a special set of tools. It is effective to capture macroscopic defects, bad joints, incorrect dimensions, inadequate surface finish, large cracks, and non-compliant parts. It is also used to detect defects in composite structures [3]. Optical-based NDE techniques, as the major subset of VE methods, offer many advantages compared to other NDE methods. In addition to resistance to electromagnetic interference, optical NDE is not limited to a specific type of material and can be used in various cases. Although the use of optical approaches is expensive, these advantages lead to a wide range of applications [10]. That being said, the VE inspection methods cannot be limited in number, where any technique using vision can be considered in the mentioned scope. However, robust and efficient implementations of VE can be obtained in the literature, such as the example provided in [11]. Researchers presented a vision measurement system that was designed to track the complete field deformations of specimens, and a quad ocular vision system to calculate the concrete column deformations. In this context, the state-of-the art of the VE system in infrastructure and concrete can be studied in detail in article [12].

2.2. Eddy Current Evaluation

Eddy-current testing offers a high degree of sensitivity for material identification and microstructure characterization [13]. As the name suggests, eddy current evaluation is based on introducing an alternating current into a conductor through a process called electromagnetic induction [3]. The interaction between the magnetic field source and the test material induces eddy currents in the test piece [14]. Inspectors can detect the presence of very small cracks by monitoring changes in the eddy current. Eddy current allows detecting cracks in a variety of conductive materials, both ferromagnetic and non-ferromagnetic. It is applied without any contact between the test object and the sensor [15]. Eddy current inspection has proven its effectiveness in defect detection. Its implementations are seen in different domains such as the aeronautics industry [16][17], nuclear industry [18][19], metallurgical industry [20][21], and transportation [22].

2.3. Ultrasonic Evaluation

Ultrasonic evaluation is based on the propagation of ultrasonic waves into an object. These high-frequency sound waves are radiated into the material to characterize the material and detect defects. It consists of several functional units such as pulser-receivers, piezoelectric transducers, and display devices. A pulsar is an electronic device used to generate high voltage electrical pulses. Using pulses, the transducer generates high-frequency ultrasonic energy. Sound energy is introduced that propagates through the material like a wave. If there is a discontinuity in the wave path such as a crack, some of the energy will be reflected by the flat surface. The reflected wave signal is converted into an electrical signal using a piezoelectric transducer and the output is displayed on the screen [23]. Surface cracks can also be detected using ultrasonic evaluation. It uses the same concept as naval SONAR. In ultrasonic evaluation, information about the ultrasonic wave, such as its reflection and scattering, is used to detect flaws in materials. The two most common forms of sound waves used in industrial inspections are the longitudinal wave and the shear wave. The traveling speed of shear waves is almost half of longitudinal waves. It was found that Rayleigh waves, which are one of the surface waves that are travelling along the solid surface, are more suitable for surface flaw detection due to their physical properties [24]. In literature, there are several implementations of ultrasonic inspection. In [25], for example, the authors suggested a system model for ultrasonic examination of smooth planar fractures in ferritic steel employing pulse-echo probes. Their suggested model predicts echo amplitudes and ranges as functions of probe location, and is implemented as a suite of adaptable and user-friendly computer programs suited for usage by practical NDE engineers, backed up by a thorough user manual. Similarly, in [26], the authors introduced Laser-EMAT (ElectroMagnetic Acoustic Transducer), an ultrasonics technology appropriate for on-line surface and interior fault detection in a steel mill. The device is designed to autonomously check steel as it travels through the steel production process at temperatures above 700 degrees Celsius. Because of its non-contact nature, it is one of the few ultrasonic systems that could ever be employed in the rigorous working environment of a steel mill.

2.4. Thermal Inspection

Thermal inspection is a method of mapping and measuring surface temperatures. It is known for its use of thermal measurements of an object and its response to a stimulus. The most commonly used tools for temperature measurements are thermal cameras. Thermal cameras have been used to diagnose electrical junctions in power transmission networks [27], monitor the thermal state of other electrical installations automatically [28], assess particular qualities in various materials, and to assess the erosion resistance of silicon rubber composites as in [29]. It has proven to be an effective and economical method for evaluating concrete [3]. Thermal non-destructive evaluation is most likely applied due to its underlying physical principles. Infrared/thermal, X-ray, electromagnetic, and ultrasonic tests use the injection of some form of energy and detect the residual energy not absorbed by the object. Defects are detected when the energy intensity varies because of the presence of defects. Its results can be affected by thermal noise, but with sufficient combination with other NDE methods, more efficient and productive results can be achieved [30].

2.5. Laser Spot Thermography

Laser spot thermography (LST) is a new infrared evaluation method for surface crack inspection. The LST method uses a laser to produce a highly localized heating spot near the crack and an infrared camera to detect the perturbation of the round lateral heat flow to reveal crack information. Fiber-guided LST systems have been developed to inspect surface cracks in metal structures. A high-power laser, a fiber delivery unit, and a specially designed optical head are used to generate a heat source for the nine-by-nine laser array points on the sample surface. Combined with an improved image processing method that uses multiple background-free images, this system was able to successfully detect and extract cracks from measured thermal images [31].

References

  1. Market Leadership—Testing, Inspection and Certification Market. Available online: https://www.marketsandmarkets.com/ResearchInsight/testing-inspection-certification-market.asp (accessed on 15 August 2022).
  2. Dwivedi, S.K.; Vishwakarma, M.; Soni, A. Advances and Researches on Non Destructive Testing: A Review. Mater. Today Proc. 2018, 5, 3690–3698.
  3. Kumar, S.; Mahto, D. Recent Trends in Industrial and other Engineering Applications of Non Destructive Testing: A Review. Int. J. Sci. Eng. Res. 2013, 4. Available online: https://engineeringresearch.org/index.php/GJRE/article/view/952 (accessed on 15 August 2022).
  4. Alotaibi, M.; Asli, B.H.S.; Khan, M. Non-Invasive Inspections: A Review on Methods and Tools. Sensors 2021, 21, 8474.
  5. Ghobakhloo, M. Industry 4.0, digitization, and opportunities for sustainability. J. Clean. Prod. 2020, 252, 119869.
  6. Lasi, H.; Fettke, P.; Kemper, H.-G.; Feld, T.; Hoffmann, M. Industrie 4.0. WIRTSCHAFTSINFORMATIK 2014, 56, 261–264.
  7. Kotsiopoulos, T.; Sarigiannidis, P.; Ioannidis, D.; Tzovaras, D. Machine Learning and Deep Learning in smart manufacturing: The Smart Grid paradigm. Comput. Sci. Rev. 2021, 40, 100341.
  8. Velíšek, K.; Holubek, R.; Sobrino, D.R.D.; Ružarovský, R.; Vetríková, N. Design of a robotized workstation making use of the integration of CAD models and Robotic Simulation software as way of pairing and comparing real and virtual environments. MATEC Web Conf. 2017, 94, 05008.
  9. Hao, R.; Lu, B.; Cheng, Y.; Li, X.; Huang, B. A steel surface defect inspection approach towards smart industrial monitoring. J. Intell. Manuf. 2021, 32, 1833–1843.
  10. Zhu, Y.-K.; Tian, G.-Y.; Lu, R.-S.; Zhang, H. A Review of Optical NDT Technologies. Sensors 2011, 11, 7773–7798.
  11. Tang, Y.; Zhu, M.; Chen, Z.; Wu, C.; Chen, B.; Li, C.; Li, L. Seismic performance evaluation of recycled aggregate concrete-filled steel tubular columns with field strain detected via a novel mark-free vision method. Structures 2022, 37, 426–441.
  12. Collao, J.; Lozano-Galant, F.; Lozano-Galant, J.A.; Turmo, J. BIM Visual Programming Tools Applications in Infrastructure Projects: A State-of-the-Art Review. Appl. Sci. 2021, 11, 8343.
  13. Zergoug, M.; Lebaili, S.; Boudjellal, H.; Benchaala, A. Relation between mechanical microhardness and impedance variations in eddy current testing. NDT E Int. 2004, 37, 65–72.
  14. Cevenini, M. Safety and Productivity Innovations in Liquid Penetrants and Magnetic Particles Testing. In Proceedings of the 19th World Conference on Non-Destructive Testing (WCNDT 2016), Munich, Germany, 13–17 June 2016.
  15. García-Martín, J.; Gómez-Gil, J.; Vázquez-Sánchez, E. Non-Destructive Techniques Based on Eddy Current Testing. Sensors 2011, 11, 2525–2565.
  16. Morozov, M.; Rubinacci, G.; Tamburrino, A.; Ventre, S. Numerical models of volumetric insulating cracks in eddy-current testing with experimental validation. IEEE Trans. Magn. 2006, 42, 1568–1576.
  17. Thollon, F.; Lebrun, B.; Burais, N.; Jayet, Y. Numerical and experimental study of eddy current probes in NDT of structures with deep flaws. NDT E Int. 1995, 28, 97–102.
  18. Chen, Z.; Miya, K. A New Approach for Optimal Design of Eddy Current Testing Probes. J. Nondestruct. Eval. 1998, 17, 105–116.
  19. La, R.; Benoist, B.; de Barmon, B.; Talvard, M.; Lengellé, R.; Gaillard, P. MESSINE, a Parametric Three-Dimensional Eddy Current Model. Res. Nondestruct. Eval. 2000, 12, 65–86.
  20. Stander, J.; Plunkett, J.; Michalson, W.; McNeill, J.; Ludwig, R. A novel multi-probe resistivity approach to inspect green-state metal powder compacts. J. Nondestruct. Eval. 1997, 16, 205–214.
  21. Institut Dr. Foerster Home Page. Available online: http://www.foerstergroup.com (accessed on 17 January 2011).
  22. Pohl, R.; Erhard, A.; Montag, H.J.; Thomas, H.M.; Wüstenberg, H. NDT techniques for railroad wheel and gauge corner inspection. NDT E Int. 2004, 37, 89–94.
  23. Roshan, C.C.; Raghul, C.; Ram, H.V.; Suraj, K.P.; Solomon, J. Non-destructive testing by liquid penetrant testing and ultrasonic testing—A review. Int. J. Adv. Res. Ideas Innov. Technol. 2019, 5, 694–697.
  24. Hishamuddin, M.A.H.; Mohd Zin, S.M.; Yusup, E.M. Non-Destructive Measurement and Evaluation of Surface Cracks Using Ultrasonic Rayleigh Waves—A Review. J. Phys. Conf. Ser. 2021, 2129, 012038.
  25. Chapman, R.K. A system model for the ultrasonic inspection of smooth planar cracks. J. Nondestruct. Eval. 1990, 9, 197–210.
  26. Baillie, I.; Griffith, P.; Jian, X.; Dixon, S. Implementing an ultrasonic inspection system to find surface and internal defects in hot, moving steel using EMATs. Insight-Non-Destr. Test. Cond. Monit. 2007, 49, 87–92.
  27. Rogler, R.D.; Lobl, H.; Schmidt, J. A diagnostic system for live electrical joints in power transmission systems. In Proceedings of the Forty-Second IEEE Holm Conference on Electrical Contacts. Joint with the 18th International Conference on Electrical Contacts, Chicago, IL, USA, 16–20 September 1996.
  28. Jadin, M.S.; Ghazali, K.H.; Taib, S. Thermal condition monitoring of electrical installations based on infrared image analysis. In Proceedings of the 2013 Saudi International Electronics, Communications and Photonics Conference, Riyadh, Saudi Arabia, 27–30 April 2013.
  29. Meyer, L.H.; Jayaram, S.H.; Cherney, E.A. A novel technique to evaluate the erosion resistance of silicone rubber composites for high voltage outdoor insulation using infrared laser erosion. IEEE Trans. Dielectr. Electr. Insul. 2005, 12, 1201–1208.
  30. Balageas, D.; Maldague, X.; Burleigh, D.; Vavilov, V.P.; Oswald-Tranta, B.; Roche, J.M.; Pradere, C.; Carlomagno, G.M. Thermal (IR) and Other NDT Techniques for Improved Material Inspection. J. Nondestruct. Eval. 2016, 35, 18.
  31. Qiu, J.; Pei, C.; Liu, H.; Chen, Z.; Demachi, K. Remote inspection of surface cracks in metallic structures with fiber-guided laser array spots thermography. NDT E Int. 2017, 92, 213–220.
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Subjects: Engineering, Mechanical
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Ali Jaber
,
Sasan Sattarpanah Karganroudi
,
Mohammad Saleh Meiabadi
,
Ahmad Aminzadeh
,
Hussein Ibrahim
,
Mehdi Adda
,
Hossein Taheri
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Update Date: 31 Oct 2022
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