Reconstruction Algorithm For Probabilistic Inspection Of Damage Research Articles

Research on spatial localization method of composite damage under strong noise

In this paper, a damage spatial imaging approach based on novel signal extraction is suggested to reconstruct the Lamb wave response signal under strong noise and realize the spatial localization of damage. First, the Variable Mode Decomposition (VMD) parameters are optimized by the improved Grey Wolf optimization method (IGWO) to decompose the response signal. To rebuild the response signal, the correlation coefficient is used to choose the optimal modal component and the residual. To give the best wavelet function and transform level for adaptive denoising of the reconstructed signal without a reference signal, an enhanced Discrete Wavelet Transform (DWT) based on Shannon entropy is proposed. To achieve damage localization imaging, a damage spatial localization model is built utilizing a reconstruction algorithm for probabilistic inspection of damage (RAPID) approach and a convolutional neural network (CNN). The suggested method may successfully increase the signal-to-noise ratio (SNR) of the reconstructed response signal and lower the error of spatial localization under strong noise through experiments. The spatial localization of composite damage using Lamb wave under strong noise is expanded in this paper.

Research on multiple damage localisation based on fusion of the Lamb wave ellipse algorithm and RAPID algorithm

Current damage localisation methods often require many sensors and complex signal processing methods. This paper proposes a fusion algorithm based on elliptical localisation and the reconstruction algorithm for probabilistic inspection of damage (RAPID) to locate and image multiple damages. Experimental verification of the damage algorithm was conducted. An ultrasonic probe was used to excite Lamb signals on an aluminium alloy plate, the ultrasonic response signals at different positions within the plate under multiple damages were measured and the constructed algorithm was employed to image the damage location. In the experiment, this method improved localisation efficiency by excluding invalid sensing paths in the sensor network, saving 31.32% of computational time. When some sensors in the sensor network were damaged, this algorithm ensured a positioning accuracy with a positioning error of 5.83 mm. Finally, the algorithm was used to locate multiple damages in the sensor network and the results showed the good robustness of the algorithm.

Modified reconstruction algorithm for probabilistic inspection of damage based on damaged virtual sensing paths

Ultrasonic guided wave is an effective approach for structural damage detection, among which the reconstruction algorithm for probabilistic inspection of damage (RAPID) is widely used. For the problem that the localization accuracy of traditional RAPID is seriously affected by the damage shape factor β, this paper proposes a modified RAPID based on damaged virtual sensing paths (DVSPs). The DVSP is determined by the time of flight (TOF) or damage index (DI) and is defined as a line of passing damage from a real actuator to a virtual sensor. Using DVSPs instead of real paths for damage localization can effectively avoid the β selection dilemma. Experiments were conducted on an aluminum plate and composite laminates. With the change of β, the average localization error does not exceed 9 mm, and the variation is less than 2 mm, while the error variance of the traditional RAPID is more than 35 mm.

Structural health monitoring of an adhesively bonded CFRP aircraft fuselage by ultrasonic Lamb Waves

The aviation industry faces the challenge of offering aircraft that are lighter, more economical, and safer. One of the solutions is to increase the use of composites. For these materials, adhesive bonding has proven to be the appropriate joining technology. To check these adhesive joints, costly and time-consuming maintenance measures are carried out. An intelligent Structural Health Monitoring (SHM) system can extend these intervals and allow the use of a predictive maintenance system. This paper describes the method of Ultrasonic Lamb Waves for monitoring a adhesively bonded Carbon Fiber Reinforced Polymer (CFRP) aircraft fuselage. Prior to this, the production of a segment of a fuselage and the characterization of the materials (CFRP and adhesive) is shown. Afterwards the method of Ultrasonic Lamb Waves with the use of piezoelectric transducers and signal processing based on the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) algorithm are explained. At the end, the experimental evaluation of an undamaged and a damaged fuselage structure is done. The results have shown the possibility of RAPID algorithm for damage detection on adhesive. An outlook on future work is given.

Influence and Compensation of Temperature Effects for Damage Detection and Localization in Aerospace Composites.

Structural Health Monitoring (SHM) of Carbon Fiber Reinforced Polymers (CFRP) has become, recently, in a promising methodology for the field of Non-Destructive Inspection (NDI), specially based on Ultrasonic Guided Waves (UGW), particularly Lamb waves using Piezoelectric Transducers (PZT). However, the Environmental and Operational Conditions (EOC) perform an important role on the physical characteristics of the waves, mainly the temperature. Some of these effects are phase shifting, amplitude changes and time of flight (ToF) variations. In this paper, a compensation method for evaluating and compensating the effects of the temperature is carried out, performing a data-driven methodology to calculate the features from a dataset of typical temperature values obtained from a thermoset matrix pristine plate, with a transducer network attached. In addition, the methodology is tested on the same sample after an impact damage is carried out on it, using RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) and its geometrical variant (RAPID-G) to calculate the location of the damage.

Damage Detection and Characterization in Composites Using a Geometric Modification of the RAPID Algorithm

Structural Health Monitoring (SHM) of aircraft structures, which are manufactured more and more using composite material, is a well-established technique for increasing reliability and reducing maintenance costs. Implementing damage inspection algorithms that run in dedicated electronic systems helps reduce big data processing time with improved results. RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) algorithm, developed some years ago, provides a technique to identify and characterize damages both in metallic and composite materials. However, this algorithm sometimes provides inaccurate predictions of the damage location, caused mainly by the influence of path intersection points among transducers, that can mask the current location of damages. This work presents a geometrical modification of standard RAPID algorithm (RAPID-G) that mitigates the influence of the intersection point between sensor paths. The results highlight that the location of damages improves significantly with this modification of the algorithm.

A study on guided wave tomographic imaging for defects on a curved structure

Guided wave tomography is a very attractive technique for online nondestructive evaluation and structural health monitoring. The reconstruction algorithm for probabilistic inspection of damage (RAPID) is an effective tomography algorithm for detecting, locating, and imaging defects. Conventional tomography imaging techniques are difficult to quantify defects in structures with curved surfaces like aircraft. It is not a complete tool for evaluation of a damaged area on a curved surface, because of insufficient guidelines for shape factor (Bata) and curvature. Probabilistic inspection of damage is used to construct tomographic images of hole defects in a 30 mm diameter and thickness 5 mm carbon steel plate and curved surface specimen. Imaging is completed using an array of 16 transducers. It is shown that defect location can be accurately determined on plate and curved surfaces. The work presented here introduces a calculation for the shape factor for evaluation of the damaged area, as well as a variable $$\beta$$ parameter technique to correct a damaged shape. An experiment is performed using the guided wave pitch-catch method to find the length of the damage on a ray path. Also, we perform research in modeling simulation and an experiment for comparison with a suggested inspection method and verify its validity. In the plate and curved surface images resulting from the advanced RAPID algorithm, the defect area and shape showed good agreement. Quantitative imaging techniques on the surface can be applied to real-time defects imaging of aircraft component monitoring.

Enhanced algorithm for damage location on composite material

Aircraft structures, which are manufactured increasingly using composite materials, present several difficulties for the location of damages using Structural Health Monitoring (SHM) techniques due to their mechanical properties (anisotropy, wave propagation, stiffness, etc.). In this study, the RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) algorithm was used to detect and locate damages in a small surface thermoplastic composite material sample, using Lamb waves generated and recorded with piezoelectric transducers (PZT).Some types of damage cause inaccurate predictions, mainly due to their size and location, in this case, especially when the damage is close to a direct path between transducers, and provides a masked detection. Our new proposal for the enhanced RAPID algorithm solves this issue, by performing a geometrical modification which corrects the elliptical distribution on the intersection points.

Application of a Probabilistic Algorithm for Ultrasonic Guided Wave Imaging of Carbon Composites

The Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) is a baseline-dependent imaging method. It utilizes a permanent array of ultrasonic transducers that covers the region of interest to interrogate the structure and estimate the presence and location of damage. The method has already proven its capability to detect different types of damage in aluminum plate structures, e.g. cracking or corrosion damage. In the present study, we apply RAPID to inspect carbon-fiber reinforced polymer (CFRP) components for the presence of impact damage and delaminations. In addition, numerical and experimental results of a baseline-free RAPID approach for the detection of nonlinear defects in CFRP will be presented. This modified RAPID draws on the Scaling Subtraction Method (SSM) which is well known from the field of nonlinear ultrasound.

Damage Detection of Composite Plates by Lamb Wave Ultrasonic Tomography with a Sparse Hexagonal Network Using Damage Progression Trends

Lamb wave based structural health monitoring shows a lot of potential for damage detection of composite structures. However, currently there is no agreement upon optimal network arrangement or detection algorithm. The objective of this research is to develop a sparse network that can be expanded to detect damage over a large area. To achieve this, a novel technique based on damage progression history has been developed. This technique gives an amplification factor to data along actuator-sensor paths that show a steady reduction in transmitted power as induced damage progresses and is implemented with the reconstruction algorithm for probabilistic inspection of damage (RAPID) technique. Two damage metrics are used with the algorithm and a comparison is made to the more commonly used signal difference coefficient (SDC) metric. Best case results show that damage is detected within 12 mm. The algorithm is also run on a more sparse network with no damage detection, therefore indicating that the selected arrangement is the most sparse arrangement with this configuration.