Signal processing methods for defect detection in multi-wire helical waveguides using ultrasonic guided waves

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University LondonNon-Destructive Testing of industrial components carries vital importance, both financially and safety-wise. Among all Non-Destructive techniques, Long Range Ultrasonic Testing utilizing the guided wave phenomena is a young technology proven to be commercially valid. Owing to its well-documented analytical models, Ultrasonic Guided Waves has been successfully applied to cylindrical and plate-like structures. Its applications to complex structures such as multi-wire cables are fairly immature, mainly due to the high complexity of wave propagation. Research performed by the author approaches the long range inspection of overhead transmission line cables using ultrasonic guided waves. Existing studies focusing on guided wave application on power cables are extremely limited in inspection range, which dramatically degrades its chances of commercialization. This thesis consists of three main chapters, all of which approaches different problems associated with the inspection of power cables. In the first chapter, a thorough analysis of wave propagation in ACSR (most widely used power cable) cables is conducted. It is shown that high frequency guided waves, by concentrating the energy on the surface layers, can travel much further in the form of fundamental longitudinal wave mode, than previous studies have shown. Defect detection studies proved the system’s capability of detecting defects which introduce either increase or decrease in cross sectional area of the cable. Results of the chapter indicate the detectability of defects as small as 4.5% of the cross sectional area through a 26.5 meter long cable without any post-processing. In the second chapter, several algorithms are proposed to increase the inspection range and signal quality. Well-documented wavelet-denoising algorithm is optimized for power cables and up to 24% signal-to-noise ratio improvement is achieved. By introducing an attenuation correction framework, a theoretical inspection range of 75 meters is presented. A new framework combining dispersion compensation and attenuation correction is proposed and verified, which shows an inspection range of 130 meters and SNR improvement up to 8 dBs. Last chapter addresses the accurate localization of structural defects. Having proven the optimum excitation and related wave propagation in ACSR cables, a system having a more complex wave propagation characteristics is studied. A new algorithm combining pulse compression using Maximal Length Sequences and dispersion compensation is applied to multi-modal signals obtained from a solid aluminum rod. The algorithm proved to be able to improve signal quality and extract an accurate location for defects. Maximal Length Sequences are compared to chirp signals in terms of SNR improvement and localization, which produced favourable results for MLS in terms of localization and for chirp in terms of SNR improvement

Eddy current defect response analysis using sum of Gaussian methods

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics

NDE: An effective approach to improved reliability and safety. A technology survey

Technical abstracts are presented for about 100 significant documents relating to nondestructive testing of aircraft structures or related structural testing and the reliability of the more commonly used evaluation methods. Particular attention is directed toward acoustic emission; liquid penetrant; magnetic particle; ultrasonics; eddy current; and radiography. The introduction of the report includes an overview of the state-of-the-art represented in the documents that have been abstracted

Ensemble Joint Sparse Low Rank Matrix Decomposition for Thermography Diagnosis System

Composite is widely used in the aircraft industry and it is essential for manufacturers to monitor its health and quality. The most commonly found defects of composite are debonds and delamination. Different inner defects with complex irregular shape is difficult to be diagnosed by using conventional thermal imaging methods. In this paper, an ensemble joint sparse low rank matrix decomposition (EJSLRMD) algorithm is proposed by applying the optical pulse thermography (OPT) diagnosis system. The proposed algorithm jointly models the low rank and sparse pattern by using concatenated feature space. In particular, the weak defects information can be separated from strong noise and the resolution contrast of the defects has significantly been improved. Ensemble iterative sparse modelling are conducted to further enhance the weak information as well as reducing the computational cost. In order to show the robustness and efficacy of the model, experiments are conducted to detect the inner debond on multiple carbon fiber reinforced polymer (CFRP) composites. A comparative analysis is presented with general OPT algorithms. Not withstand above, the proposed model has been evaluated on synthetic data and compared with other low rank and sparse matrix decomposition algorithms

Passive low frequency RFID for non-destructive evaluation and monitoring

Ph. D ThesisDespite of immense research over the years, defect monitoring in harsh environmental conditions still presents notable challenges for Non-Destructive Testing and Evaluation (NDT&E) and Structural Health Monitoring (SHM). One of the substantial challenges is the inaccessibility to the metal surface due to the large stand-off distance caused by the insulation layer. The hidden nature of corrosion and defect under thick insulation in harsh environmental conditions may result in it being not noticed and ultimately leading to failures. Generally electromagnetic NDT&E techniques which are used in pipeline industries require the removal of the insulation layer or high powered expensive equipment. Along with these, other limitations in the existing techniques create opportunities for novel systems to solve the challenges caused by Corrosion under Insulation (CUI). Extending from Pulsed Eddy Current (PEC), this research proposes the development and use of passive Low Frequency (LF) RFID hardware system for the detection and monitoring of corrosion and cracks on both ferrous and non-ferrous materials at varying high temperature conditions. The passive, low cost essence of RFID makes it an enchanting technique for long term condition monitoring. The contribution of the research work can be summarised as follows: (1) implementation of novel LF RFID sensor systems and the rig platform, experimental studies validating the detection capabilities of corrosion progression samples using transient feature analysis with respect to permeability and electrical conductivity changes along with enhanced sensitivity demonstration using ferrite sheet attached to the tag; (2) defect detection using swept frequency method to study the multiple frequency behaviour and further temperature suppression using feature fusion technique; (3) inhomogeneity study on ferrous materials at varying temperature and demonstration of the potential of the RFID system; (4) use of RFID tag with ceramic filled Poly-tetra-fluoro-ethyulene (PTFE) substrate for larger applicability of the sensing system in the industry; (5) lift-off independent defect monitoring using passive sweep frequency RFID sensors and feature extraction and fusion for robustness improvement. This research concludes that passive LF RFID system can be used to detect corrosion and crack on both ferrous and non-ferrous materials and then the system can be used to compensate for temperature variation making it useful for a wider range of applications. However, significant challenges such as permanent deployment of the tags for long term monitoring at higher temperatures and much higher standoff distance, still require improvement for real-world applicability.Engineering and Physical Sciences Research Council (EPSRC) CASE, National Nuclear Laboratory (NNL)