Key Engineering Materials Vols. 569-570

Abstract: The study deals with the opportunities for the assessment of damage to blades in low-pressure steam turbine stages under operation. So far existing methods are based on measurements and evaluation of blade vibrations. Calculations of fatigue cycles are used as a basis for an estimate of the residual life of the blades. A new approach using the analysis of impulse blade signals generated by non-contact stator sensors was applied. Basis for the assessment of blade damage are static characteristics and mutual position of blades. Geometrical and mechanical characteristics of blades change due to creation and progress of a crack. The presence of the crack leads to a change in position between adjacent blades. This method has been applied and verified by long-term measurements at the nuclear power plant Temelin. Other static methods based on blade untwisting and elongation are suggested for monitoring the state of turbine blades.

Abstract: In this paper the IDDM (Interpolation Damage Detection Method), recently proposed as a speedy damage detection and localization technique, is applied to the numerical model of a cable suspended bridge derived from the ANSYS model of the Shimotsui-Seto Bridge in Japan (940m length of the main span). The wind excitation is simulated as a spatially correlated process acting in the horizontal direction, transversal to the deck. The bridge is assumed to be monitored by sensors located at the nodes of the model along the longitudinal axis, and recording the absolute acceleration of the bridge deck in the transversal direction Noise in recorded responses can reduce the sensitivity of the method to damage. The influence of noise on the results of the damage detection method is herein investigated by adding a white-noise signal to the structural responses. The mutual relationship between level of noise, intensity of damage and lengths of recorded signals is also investigated with reference to various damage scenarios.

Abstract: High energy consumption, excessive data storage and transfer requirements are prevailing issues associated with structural health monitoring (SHM) systems, especially with those employing wireless sensors. Data compression is one of the techniques being explored to mitigate the effects of these issues. Compressive sensing (CS) introduces a means of reproducing a signal with a much less number of samples than the Nyquist's rate, reducing the energy consumption, data storage and transfer cost. This paper explores the applicability of CS for SHM, in particular for damage detection and localization. CS is implemented in a simulated environment to compress SHM data. The reconstructed signal is verified for accuracy using structural response data obtained from a series of tests carried out on a reinforced concrete (RC) slab. Results show that the reconstruction was close, but not exact as a consequence of the noise associated with the responses. However, further analysis using the reconstructed signal provided successful damage detection and localization results, showing that although the reconstruction using CS is not exact, it is sufficient to provide the crucial information of the existence and location of damage.

Abstract: The employment of a large number of embedded sensors in advanced monitoring systems becomes more common, enabling in-service detection, localization and assessment of defects in mechanical, civil and aerospace structures. These sensors could be optical fibre sensors, accelerometers, strain gauges or piezoelectric wafer active sensors (PWAS). As the latter are quite popular, due to its multipurpose application as actuators and sensors and its low cost, this type will be investigated. Within this paper a possible approach of sensor performance is presented. The method uses the coupled electro-mechanical admittance to detect damage of the PWAS and its bonding layer. The help of a temperature dependent theoretical model provides for influences of changing environmental and operational conditions. The model will be compared with FEM-results, before showing the successful application on experimental results.

Abstract: Degradation phenomenacan affect civil structures over their lifespan. The recent advances innanotechnology and sensing allow to monitor the behaviour of a structure,assess its performance and identify damage at an early stage. Thus, maintenanceactions can be carried out in a timely manner, improving structural reliabilityand safety. Structural Health Monitoring (SHM) is traditionally performed at aglobal level, with a limited number of sensors distributed over a relativelylarge area of a structure. Thus, only major damage conditions are detectable. Densesensor networks and innovative structural neural systems, reproducing thestructure and the function of the human nervous system, may overcome thisdrawback of current SHM systems. Miniaturization and embedment are keyrequirements for successful implementation of structural neural systems. Carbonnanotubes (CNT) can play an attractive role in the development of embeddedsensors and smart structural materials, since they provide to traditionalmaterials like cement both structural capability and measurable response toapplied stresses, strains, cracks and other flaws. In this paper the mainresults of an extensive literature review about CNT/cement composites and theirself-sensing capabilities are summarized and critically revised. The analysisof experimental results and theoretical developments provides useful designcriteria for the fabrication of CNT/cement composites optimized for SHM applicationsin civil engineering.

Abstract: The availability of a suitable data acquisition sensor network is a key implementation issue to link models with real world structures. Non-contact displacement sensors should be preferred since they do not change the system properties. A two-dimensional vision-based displacement measurement sensor is the focus of this contribution. In particular, the perspective distortion introduced by the angle between the optic axis of the camera and the normal to the plane in which the structural system deforms is considered. A two-dimensional affine transformation is utilized to eliminate the distortion from the recorded to the distortion-free image. The results of a laboratory experiment show the potential of the proposed approach.

Abstract: The main rotor accounts for the largest vibration source for helicopter fuselage and components. However, accurate blade monitoring has been limited due to the practical restrictions on instrumenting rotating blades. The use of Wireless Sensor Networks (WSNs) for real time vibration monitoring promises to deliver a significant contribution to rotor performance monitoring and blade damage identification. This paper discusses the main technological challenges for wireless sensor networks for vibration monitoring on helicopter rotor blades. The first part introduces the context of vibration monitoring on helicopters. Secondly, an overview of the main failure modes for rotor and blades is presented. Based on the requirements for failure modes monitoring, a proposition for a multipurpose sensor network is presented. The network aims to monitor rotor performance, blade integrity and damage monitoring at three different scales referred to as macro layer, meso layer and micro layer. The final part presents the requirements for WSNs design in relation with sensing, processing, communication and actuation. Finally power supply aspects are discussed.

Abstract: This paper reports the analysis of the effectiveness of the application of rotation rate sensors in structural damage identification problem using harmonic vibrations for plexiglass models of cantilever beams. The two types of sensors are applied: angular rate sensors and conventional translational, piezoelectric accelerometers. The amplitudes of dynamic response under harmonic kinematic excitations were subsequently used in the stiffness reconstruction procedure. Particularly promising results are obtained by using only rotation rate sensors in the reconstruction procedure.

Abstract: The number of vibration response sensors required for structural damage detection andprecise localization on a continuous structural topology is investigated. For damage detection thestate–of–the–art of vibration based methods need a required number of sensors q that may be “low”compared to the number of structural modes m, that is q << m. Yet, the opposite is generally suggestedfor precise damage localization, that is q > m. In this study the hypothesis that a “low” numberof vibration response sensors, q << m, may, under certain conditions, suffice for precise damage localization,is postulated. This hypothesis is “proven” experimentally by demonstrating that preciselocalization is indeed possible using a single vibration response sensor and an advanced StructuralHealth Monitoring methodology on a laboratory 3D truss structure.

Abstract: Polymer closed cell foam beam specimens manufactured from H100 Divinycell (Diab) are tested in four point bend at three loading speeds using a specially designed rig and an Instron VHS test machine. Synchronised high speed images are captured using white light and infra-red thermography (IRT) to obtain the mid-point full-field deflection and strains using digital image correlation (DIC) along with the temperature evolutions. There is a marked increase in the maximum load to failure with loading rate and the optical techniques provide an opportunity to analyse the strain and temperature evolution within the specimens.