Key Engineering Materials Vol. 518

Abstract: Non-contact optical/laser measuring techniques are very attractive in many engineering applications. The paper demonstrates examples related to structural health monitoring. Various methods based on strain, vibration and ultrasound measurements are presented together with relevant references. Applications examples utilise in-plane and out-of-plane measurements taken by 1-D and 3-D laser Doppler vibrometers.

Abstract: This article describes an example analysis of safety against derailment of a railway vehicle. The analysis is based on the experimental data recorded during measurement of the wheel-rail interaction forces and lateral accelerations. The data is used for the calculation of two safety against derailment indicators and then the indicators are compared to each other. The first indicator is the ratio of the lateral to vertical wheel-rail forces Y/Q, based on the Nadal criteria. The second indicator is given in the energy description. In this description, the derailment of a railway vehicle depends on the amount of the work that has been done by the total lateral force acting on the single wheelset. The second indicator can be particularly convenient for a railway vehicle condition monitoring system, because it does not require the measurement of the contact forces.

Abstract: The implementation of selected full-field optical methods for monitoring and measurements of displacements, strains and shape of structures in power plants are reported. Digital Image Correlation, Fringe Projection and integrated thermovision-DIC method have been utilized for monitoring and control of repair processes of selected elements during general overhauls in power plants, including control of welds annealing process in boiler drum and steam pipes and measurements of geometry changes of steam pipes in “hot” and “cold” states. The experience gathered during the measurement sessions in power plants has been used for enhancement and adaptation of typical architecture of measurement systems to demanding and difficult industrial environment conditions. The measurements had been carried out in different power plants located in Poland. The possible future application of full-field optical measurement methods as the alternative to standard techniques (ultrasound, X-ray, strain gauges) and their advantages and disadvantages are discussed.

Abstract: The Structural Health Monitoring process includes several steps like feature extraction and probabilistic decision making, which need some form of data fusion and information condensation. These take place after data acquisition and before being able to decide, if a monitored structure has faced damage. Although feature selection is an important step, the processing and suitable preparation of these data are significant, influencing the potential of decision making in various ways. With Self-Organizing Maps (SOM) a multi-purpose instrument for these tasks of pattern recognition and data interpretation is presented here. Self-Organizing Maps belong to the group of artificial neural networks and by using the special map character provide the opportunity of additional visualization. Especially when monitoring a structure over a long period of time, environmental changes often occur, which can mask the effects of damage on the dynamic behavior of the structures. As one potential application of SOM, the possibility of distinguishing between environmental changes and damage of the structure is shown. In this application a self-organizing network is trained with data of the undamaged structure and via calculation of the distance to the map a damage indicator is developed. Moreover, the distinction between different damage modes of piezoelectric sensors is presented using SOM as a tool of pattern recognition and visualization. This application uses data recorded from different damage modes extracted from one specimen of a piezoelectric element. The trained network can be compared with other piezoelectric elements mounted in a similar way to be able to detect possible sensor damage. This helps avoiding false alarms even under changing environmental conditions. Both applications have been successfully used to analyze experimental data on coupon level showing the applicability of the presented concepts.

Abstract: Fault diagnosis is important to avoid unforeseen failures of IC engines, but normally requires an expert to interpret analysis results. Artificial Neural Networks are potential tools for the automated fault diagnosis of IC engines, as they can learn the patterns corresponding to various faults. Most engine faults can be classified into two categories: combustion faults and mechanical faults. Misfire is a typical combustion fault; piston slap and big end bearing knock are common mechanical faults. The automated diagnostic system proposed in this paper has three main stages, each stage including three neural networks. The first stage is the fault detection stage, where the neural networks detect whether there are faults in the engine and if so which kind. In the second stage, based on the detection results, the severity of the faults was identified. In the third stage, the neural networks localize which cylinder has a fault. The critical thing for a neural network is its input feature vector, and a previous study had indicated a number of features that should differentiate between the different faults and their location, based on advanced signal processing of the vibration signals measured for different normal and fault conditions. In this study, an advanced feature selection technology was employed to select the significant features as the inputs to networks. The input vectors were separated into two groups, one for training the network, and the other for its validation. Finally it has been demonstrated that the neural network based system can automatically differentiate and diagnose a number of engine faults, including location and severity.

Abstract: Composite patch repairs are being increasingly used throughout bridge structures in the UK. These patches offer a convenient and strong repair providing that the bond used to adhere the patch to the structure retains its integrity. Acoustic emission (AE), a passive approach and Acousto-Ultrasonic (AU), an active approach offer two methodologies for monitoring the structural bond and ensuring the patch repair remains effective. An experimental program was developed to assess the suitability of using AE and AU for monitoring the bond. Two concrete beams were manufactured and pre-cracked in three point bending prior to being repaired using a bonded composite patch. Two static tests were then completed to assess the performance of the two techniques for monitoring the bond. Results were compared with strain gauges adhered to the bonded patch and visual observation. For active monitoring a baseline of signals were captured at a known load and post damage a further series was captured at the same load. The signals sets were then compared using a cross correlation function technique. A simple accumulative acoustic energy analysis was then completed for the passive data. Results demonstrated that both techniques can be utilised to monitor the bonded structure. By comparing the results with those recorded by the strain gauges and visual inspection it was possible to demonstrate the successful effectiveness of the techniques for detecting global damage but specific debonding events would require further investigations.

Abstract: Condition monitoring and fault detection systems are becoming increasingly important in rail vehicles maintenance and operation, ensuring safety and reliability improvement. Light rail systems are not the main target for this trend, because of low operational speed and lower safety factors. Nevertheless public transport operators begin to pay a closer attention to the technical state monitoring of vehicle and track, in order to reduce maintenance cost and increase safety and ride comfort for passengers, which is an important challenge for public transport competitiveness in XXI century. The paper describes the main concept of the innovative on-board condition monitoring system for light rail vehicle and track. Functional requirements, assumptions and procedures are described, as well as the on-board data acquisition unit with necessary transducers, which number, function and technical parameters were optimized during the research phase of the project. The prototype of the presented system is now being tested in normal operating conditions.

Abstract: The paper develops a simplified two-degree-of-freedom gear model that simulates vibration signals under operational conditions similar to those of wind turbine gearboxes. Nonlinear characteristics were included in the model in order to obtain more realistic results. The two types of faults examined in this study are common periodic gear tooth faults and intermittent gear tooth faults. The latter type of faults appears to be a novel idea in the condition monitoring field. Transient loads are also taken into consideration in this study since such loads are commonly observed in wind turbine systems, and make it even more difficult to detect damage. The analysis of the obtained signals is done using a relatively new method, the Empirical Mode Decomposition (EMD) that works well for nonstationary and nonlinear signals.

Abstract: Guided waves (GW) based methods are a promising tool for structural health monitoring (SHM) of plate-like metallic and composite structures in which high safety standards are required. In this paper we present research with the aim to design and manufacture a prototype of Lamb waves (LW) SHM system. Two approaches can be applied for SHM of plate-like structures. One of them can be based on a sparse array and damage imaging involving incoherent summation of signals envelope. The second approach involves phased arrays with transducers spaced at a distance lower than half wavelength of the excited Lamb-mode. The influence of an arrays parameters on beamforming of Lamb waves is discussed in the case of linear array. It appears that an unequivocal localization of damage on a plate requires a 2D arrays topology; therefore a star-shaped active array was designed and manufactured for the developed SHM system. Two signal processing approaches were applied for that array, the standard one, based on the delay and sum (DAS) synthetic aperture focusing scheme, and the second one, using a self-focusing technique to obtain the separate images for each scatterer existing in the plate.