Transfer Learning-Based Crack Detection by Autonomous UAVs

Unmanned Aerial Vehicles (UAVs) have recently shown great performance collecting visual data through autonomous exploration and mapping in building inspection. Yet, the number of studies is limited considering the post processing of the data and its integration with autonomous UAVs. These will enable huge steps onward into full automation of building inspection. In this regard, this work presents a decision making tool for revisiting tasks in visual building inspection by autonomous UAVs. The tool is an implementation of fine-tuning a pretrained Convolutional Neural Network (CNN) for surface crack detection. It offers an optional mechanism for task planning of revisiting pinpoint locations during inspection. It is integrated to a quadrotor UAV system that can autonomously navigate in GPS-denied environments. The UAV is equipped with onboard sensors and computers for autonomous localization, mapping and motion planning. The integrated system is tested through simulations and real-world experiments. The results show that the system achieves crack detection and autonomous navigation in GPS-denied environments for building inspection

Detection of curved lines with B-COSFIRE filters: A case study on crack delineation

The detection of curvilinear structures is an important step for various computer vision applications, ranging from medical image analysis for segmentation of blood vessels, to remote sensing for the identification of roads and rivers, and to biometrics and robotics, among others. %The visual system of the brain has remarkable abilities to detect curvilinear structures in noisy images. This is a nontrivial task especially for the detection of thin or incomplete curvilinear structures surrounded with noise. We propose a general purpose curvilinear structure detector that uses the brain-inspired trainable B-COSFIRE filters. It consists of four main steps, namely nonlinear filtering with B-COSFIRE, thinning with non-maximum suppression, hysteresis thresholding and morphological closing. We demonstrate its effectiveness on a data set of noisy images with cracked pavements, where we achieve state-of-the-art results (F-measure=0.865). The proposed method can be employed in any computer vision methodology that requires the delineation of curvilinear and elongated structures.Comment: Accepted at Computer Analysis of Images and Patterns (CAIP) 201

Vibration-based damage detection in an aircraft wing scaled model using principal component analysis and pattern recognition

This study deals with vibration-based fault detection in structures and suggests a viable methodology based on principal component analysis (PCA) and a simple pattern recognition (PR) method. The frequency response functions (FRFs) of the healthy and the damaged structure are used as initial data. A PR procedure based on the nearest neighbour principle is applied to recognise between the categories of the damaged and the healthy wing data. A modified PCA method is suggested here, which not only reduces the dimensionality of the FRFs but in addition makes the PCA transformed data from the two categories more differentiable. It is applied to selected frequency bands of FRFs which permits the reduction of the PCA transformed FRFs to two new variables, which are used as damage features. In this study, the methodology is developed and demonstrated using the vibration response of a scaled aircraft wing simulated by a finite element (FE) model. The suggested damage detection methodology is based purely on the analysis of the vibration response of the structure. This makes it quite generic and permits its potential development and application for measured vibration data from real aircraft wings as well as for other real and complex structures

A phased array-based method for damage detection and localization in thin plates

A method for damage localization based on the phased array idea has been developed. Four arrays oftransducers are used to perform a beam-forming procedure. Each array consists of nine transducersplaced along a line, which are able to excite and register elastic waves. The A0 Lamb wave mode hasbeen chosen for the localization method. The arrays are placed in such a way that the angulardifference between them is 458 and the rotation point is the middle transducer, which is common for allthe arrays. The idea has been tested on a square aluminium plate modeled by the Spectral Element Method. Two types of damage were considered, namely distributed damage, which was modeled asstiffness reduction, and cracks, modeled as separation of nodes between selected spectral elements.The plate is excited by a wave packet. The whole array system is placed in the middle of the plate.Each linear phased array in the system acts independently and produces maps of a scanned fieldbased on the beam-forming procedure. These maps are made of time signals (transferred to spacedomain) that represent the difference between the damaged plate signals and those from the intactplate. An algorithm was developed to join all four maps. The final map is modified by proposed signal processing algorithm to indicate the damaged area of the plate more precisely. The problem fordamage localization was investigated and exemplary maps confirming the effectiveness of theproposed system were obtained. It was also shown that the response of the introduced configurationremoves the ambiguity of damage localization normally present when a linear phased array is utilized.The investigation is based exclusively on numerical data

Fractoluminescence characterization of the energy dissipated during fast fracture of glass

Fractoluminescence experiments are performed on two kinds of silicate glasses. All the light spectra collected during dynamic fracture reveal a black body radiator behaviour, which is interpreted as a crack velocity-dependent temperature rise close to the crack tip. Crack velocities are estimated to be of the order of 1300 m.s$^{-1}$ and fracture process zones are shown to extend over a few nanometers.Comment: Accepted for publication in Europhysics Letters; 5 pages; 4 figure