Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Detection of cracks in scratching tests in ceramic materials through acoustic emission

The mechanisms of material removal and the interactions among scratches performed in ceramic materials were investigated using acoustic emission signals, and scanning electron microscopy, in scratching experiments. Several testing conditions were used to produce different types of removing mechanism on a glass as well as on a polycrystalline alumina sample composed by heterogeneous grain size. It is known that the material removing process on a polycrystalline ceramic involves intergranular microfracture and grain dislodgement, unlike the chipping produced by the extension of lateral cracks in non-granular materials, such as glass. Distinct settings for velocities, loads, and two types of diamond indenter were tested. The material removal was carried out by three different methods of scratching: single passes, repeated overlapping passes, and parallel scratches. As a general result, there was a clear relationship between the acoustic emission signals and the damage intensity occurred in the material removal. More specifically, there were differences in the acoustic emission signal levels in the scratches made on the alumina and on the glass owing to the material removal mechanisms associated with the structure of these materials. A gradual increase in the acoustic emission levels was observed when the number of repeated passes was increased as a result of the damage accumulation process followed by severe material removal. It was also noticed that the acoustic emission signals were capable of reflecting the interactions between two parallel scratches.

Application of a model updating technique for health condition monitoring and damage detection of flexible structures

This paper discusses the application of a damage detection methodology to monitor the location and extent of partial structural damage. The methodology combines, in an iterative way, the model updating technique based on frequency response functions (FRF) with monitoring data aiming at identifying the damage area of the structure. After the updating procedure reaches a good correlation between the models, it compares the parameters of the damage structure with those of the undamaged one to find the deteriorated area. The influence of the FEM mesh size on the evaluation of the extent of the damage has also been discussed. The methodology is applied using real experimental data from a spatial frame structure.

Neural network detection of grinding burn from acoustic emission

An artificial neural network (ANN) approach is proposed for the detection of workpiece `burn', the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.

Lead zirconate titanate/polyurethane (PZT/PU) composite for acoustic emission sensors

Piezoelectric composite, made from ferroelectric ceramic lead zirconate titanate (PZT) and vegetable based polyurethane (PU) polymer, was doped with a semiconductor filler, graphite. The resulting composite (PZT/C/PU) with 49/1/50- vol. % composition could be poled at lower field and shorter time due to the increased conductivity of the polymer phase following the introduction of graphite. The PZT/C/PU composite showed higher pyroelectric coefficient in comparison with the undoped PZT/PU composite with 50/50-vol. % composition. Also, the PZT/C/PU composite has shown the ability to detect both extensional and flexural modes of simulated acoustic emission (AE) at a distance up to 8.0 m from the source, thus indicating that it may be used for detection of structural damages.

Calcium modified lead titanate/poly-ether-ether-ketone composite for acoustic emission sensors

Composites made of calcium modified lead titanate ceramic powder and poly (ether-ether-ketone) high performance polymer matrix were prepared in the film form using a hot press. The acoustic and electromechanical properties of the composites have been determined using the ultrasonic immersion technique and piezoelectric spectroscopy, respectively. The composite film with 60 - 40 vol.% PTCa/PEEK was tested as acoustic emission detector. Preliminary results shown that the piezo composite can be used as sensor to evaluate the behavior of materials.

PTCa/PEEK composite acoustic emission sensors

Composites made of Calcium-modified lead titanate (PTCa) and poly (ether-etherketone) (PEEK) high performance polymer matrix were prepared in the film form using a hot press. The ceramic volume fraction reaches up to 60 percent providing a composite with 0-3 and 1-3 mixed connectivities due to the high ceramic content and the resulting materials could be considered PEEK-bonded PTCa particulate composite. The composites were characterized using piezoelectric spectroscopy and ultrasonic immersion techniques. Values up to 38.5 pC/N were obtained for the longitudinal d33 piezoelectric coefficient. The composite was surface-mounted on a carbon fiber plate-like specimen and the ability of the PTCa/PEEK composite to detect acoustic emission (AE) is reported. © 2006 IEEE.

Full correction for spatially distributed speed-of-sound in echo ultrasound based on measuring aberration delays via transmit beam steering

Aberrations of the acoustic wave front, caused by spatial variations of the speed-of-sound, are a main limiting factor to the diagnostic power of medical ultrasound imaging. If not accounted for, aberrations result in low resolution and increased side lobe level, over all reducing contrast in deep tissue imaging. Various techniques have been proposed for quantifying aberrations by analysing the arrival time of coherent echoes from so-called guide stars or beacons. In situations where a guide star is missing, aperture-based techniques may give ambiguous results. Moreover, they are conceptually focused on aberrators that can be approximated as a phase screen in front of the probe. We propose a novel technique, where the effect of aberration is detected in the reconstructed image as opposed to the aperture data. The varying local echo phase when changing the transmit beam steering angle directly reflects the varying arrival time of the transmit wave front. This allows sensing the angle-dependent aberration delay in a spatially resolved way, and thus aberration correction for a spatially distributed volume aberrator. In phantoms containing a cylindrical aberrator, we achieved location-independent diffraction-limited resolution as well as accurate display of echo location based on reconstructing the speed-of-sound spatially resolved. First successful volunteer results confirm the clinical potential of the proposed technique.

Low-speed longitudinal controllers for mass-produced cars: A comparative study

Four longitudinal control techniques are compared: a classical Proportional-Integral (PI) control; an advanced technique-called the i-PI-that adds an intelligent component to the PI; a fuzzy controller based on human experience; and an adaptive-network-based fuzzy inference system. The controllers were designed to tackle one of the challenging topics as yet unsolved by the automotive sector: managing autonomously a gasoline-propelled vehicle at very low speeds. The dynamics involved are highly nonlinear and constitute an excellent test-bed for newly designed controllers. A Citroën C3 Pluriel car was modified to permit autonomous action on the accelerator and the brake pedals-i.e., longitudinal control. The controllers were tested in two stages. First, the vehicle was modeled to check the controllers' feasibility. Second, the controllers were then implemented in the Citroën, and their behavior under the same conditions on an identical real circuit was compared.

Optimisation of a Low-Speed Wind Tunnel. Analysis and Redesign of Corner Vanes.

This paper includes the experimental study, analysis, redesign and subsequent test of the parts of a closed circuit, low speed wind tunnel which are relevant in terms of total pressure loss. The objective is to lower the energy consumption of this system for given conditions in test chamber, so as to reduce the operational costs. In order to achieve this objective, several tasks were performed as the text shows in its different parts. For these tasks, the ETSIAE wind tunnel was used, although the results of this work can be extrapolated to any wind tunnel with the same characteristics. Part II presents a theoretical previous study of the general running of a closed circuit, low speed wind tunnel, as well as the followed procedure to conduct experimental tests for obtaining the total pressure loss in its parts. Results from these tests and their analysis are included in this part. In part III, the analysis of the influence of corner 1 on the pressure loss takes place. As it is said in this part, corner 1 has great importance in the total pressure loss of the wind tunnel. Therefore, it is the first part that should be modified in order to improve the performances of the wind tunnel. During part IV, an optimised guide vane is designed in order to reduce the pressure loss in corner 1 of the wind tunnel. Software MISES is used to achieve this goal by means of selecting the optimum guide vane. In order to introduce the new guide vane in wind tunnels with affordable costs, the easily constructable criterion is kept during design. For this reason, the guide vane will consist of simple aerodynamic contours. Part V includes some possible improvements for the proposed guide vane, in order to evaluate if there is room for improvement in its design. Finally, part VI includes the tests that were conducted in the wind tunnel with the new guide vane cascade and the analysis of their results, in order to asses whether the proposed design fulfills the requirement of lowering the total pressure loss in the wind tunnel. Part VII gathers the main ideas resulting from the whole work.

Ensayo no destructivo de soldaduras en pernos conectores mediante inspección acústica = Non-destructive test of welding headed studs through acoustic emission

Los pernos conectores aportan múltiples ventajas de uso, entre las que se encuentra el elevado margen de seguridad que ofrecen sus soldaduras ejecutadas mediante arco eléctrico. Estas soldaduras, aunque ampliamente fiables, son difícilmente comprobadas mediante ensayos no destructivos. Aparte de la inspección visual, que aporta gran información sobre la calidad de ejecución de la soldadura, el resto de ensayos no destructivos (líquidos penetrantes, partículas magnéticas, ultrasonidos, radiografías, etc.) resultan inviables en estos elementos. Por otro lado, los ensayos acústicos de piezas metálicas han existido siempre. Su comprobación se basaba en el análisis por medio de ¿un oído fino¿ del sonido resultante tras ser golpeado el elemento a evaluar. Con estas premisas se plantea el presente estudio de inspección de las soldaduras en pernos conectores mediante su espectro acústico. Analíticamente, la investigación se ha centrado en el cálculo informático de los primeros modos propios de vibración mediante elementos finitos. Se han modelizado diferentes grados de penetración de la soldadura mediante la modificación de las condiciones de contorno. Se ha observado que variando el número de movimientos coaccionados en los nodos pertenecientes a la soldadura se produce una reducción en su frecuencia de vibración.

Field-based models for low speed switched reluctance machine designs

Trabalho apresentado na Conferência CPE-POWERENG 2016, 29 junho a 01 de julho 2016, Bydgoszcz, Polónia