Key Engineering Materials Vols. 413-414

Abstract: Inspections of Sweden’s longest suspension bridge, the approximately ten years old High Coast Suspension Bridge, have shown that the main bridge bearings have been seriously affected by wear. A monitoring program was therefore initiated in 2005 to measure actual vertical loads acting on the bearings as well as the tension in the first hangers of the bridge. This article describes the instrumentation and the calibration process. Interesting results from several months of monitoring are presented. Results show that the measured loads on the bearings due to permanent loads are in very good agreement with what was predicted during design. However, very large loads and large dynamic effects were registered from passing lorries.

Abstract: Longitudinal vibration mode is conveniently used for damage localization and detection in truss structure. However, a satisfactory piezoelectric impedance response due to longitudinal modes is not so easy to obtain in practical applications. The objective of this paper is to investigate how to obtain the impedance response of longitudinal modes with a piece of PZT transducer. In this case various vibration modes will be excited by unilaterally bonded PZT transducer, so the observation of longitudinal modes becomes complicated. In this paper, the effect of parameters of PZT transducer such as the length and attachment position is discussed in detail. Through selecting a suitable size and attachment position, the impedance response of expected longitudinal modes can be generated. An example for generating impedance peaks of specified longitudinal mode in fixed-fixed beam is given to demonstrate its validity.

Abstract: Particle impact damping (PID) is a technique of achieving high structural damping with small metallic particles embedded within a cavity that is attached to vibrating structure. This is a highly non-linear damping mechanism in which energy dissipation is primarily related to friction and impact phenomena. In this work a simple yet detailed analytical model is presented to study PID in two dimensions under transient vibrations. Normal as well as oblique impacts are considered. The effect of cavity size and acceleration amplitude on PID is studied and the results are supported by experiments. Fairly good agreement is found between the theory and the experiment.

Abstract: The concept that changes in the dynamic behaviour of a rotor could be used for general fault detection and monitoring is well established. Current methods rely on the response of the machine to unbalance excitation during run-up, run-down or normal operation, and are mainly based on pattern recognition approaches. Of all machine faults, probably cracks in the rotor pose the greatest danger and research in crack detection has been ongoing for the past 30 years. For large unbalance forces the crack will remain permanently open and the rotor is then asymmetric, which can lead to stability problems. If the static deflection of the rotor due to gravity is large then the crack opens and closes due to the rotation of the shaft (a breathing crack), producing a parametrically excited dynamical system. Although monitoring the unbalance response of rotors is able to detect the presence of a crack, often the method is relatively insensitive, and the crack must be large before it can be robustly detected. Recently methods to enhance the quality of the information obtained from a machine have been attempted, by using additional excitation, for example from active magnetic bearings. This research is directed towards the concept of a smart rotating machine, where the machine is able to detect and diagnose faults and take action automatically, without any human intervention. This paper will consider progress to date in this area, with examples, and consider the prospects for future development.

Abstract: A genetic algorithm-support vector regression model (GA-SVR) is proposed for machine performance degradation prediction. The main idea of the method is firstly to select the condition-sensitive features extracted from rolling bearing vibration signals using Genetic Algorithm to form a condition vector. Then prediction model is established for each feature time series. And the third step is to establish support vector regression models to obtain prediction result in each series. Finally, the condition prognosis can be obtained through combing all components to form a condition vector. Vibration data from a rolling bearing bench test process are used to verify accuracy of the proposed method. The results show that the model is an effective prediction method with a higher speed and a better accuracy.

Abstract: The concept of harvesting energy is not a new one: there has been an interest in this area for around 10 years. Devices typically use either vibration (rigid body motion) or thermal gradients and can harvest sufficient energy to power telemetry, small devices or to charge a battery or capacitance device. However, for the new generation of aircraft, (both fixed wing and rotating) there is now an urgent need to develop energy harvesting systems in order to provide localised power for sensors in structural health monitoring systems (SHM). By implementing SHM, aircraft manufacturers can benefit from improved safety, reduced maintenance and extended aircraft life. The work presented examines the feasibility of designing an energy harvesting system powered by the vibrations of aircraft panels generated in flight. PZT (lead zirconate titanate) harvesters are bonded to an aluminium alloy panel, representative of an aircraft wing panel which is vibrated across a range of amplitudes (up to + 0.2mm) and frequencies (up to 300Hz). By recording voltage and current outputs from each harvester, generated power is calculated which when normalised for area and mass indicates values of up to 7.0 Wm-2 and 2.5Wkg-1 respectively, representing mechanical to electrical energy conversion efficiencies of up to 35% dependant on frequency of vibration. From these values it is estimated that a harvester area of down to 71cm2 or mass of as little as 20g is necessary to meet the current minimum power requirements of SHM systems of 50mW. With predicted reductions in sensor power consumption indicating system power requirements in the order of 0.1-1mW, this work shows that piezoelectric energy harvesting has future potential for powering aerospace SHM systems.

Abstract: In the paper it is proposed to use fibre Bragg grating (FBG) sensors to monitor the deformation and strain in a woven textile. Non-contact digital image correlation (DIC) is used to validate the results. The principal objective of the work in this paper is to identify a suitable adhesive for attaching the FBG sensors to tapestries and textiles. To do this, the interfacial interactions of the optical fibre, the textile material and the necessary adhesive must be considered. The performance of two types of adhesive are studied: a PVA conservation adhesive and a two-part epoxy adhesive Araldite 2015. The effect of the application of the adhesives on the mechanical response of the textile is investigated. Full-field stain maps are obtained from the DIC and are used as the basis to characterise the behaviour of the FBG sensors/adhesive system. The strain transfer coefficients and a reinforcement factor are determined under quasi-static conditions. It is shown that the local reinforcement introduced is more significant in the specimen with the FBG bonded using the Araldite adhesive than those with conservation adhesives. Nevertheless, the Araldite adhesive has a better strain transfer coefficient than the conservation adhesive, although not as high as that expect with conventional engineering materials.

Abstract: In structural health monitoring (SHM) of civil structures, data compression is often needed for saving the cost of data transfer and storage because of the large volumes of sensor data generated from the monitoring system. The traditional framework for data compression is to first sample the full signal, then to compress it. Recently, a new data compression method named compressive sampling (CS) has been presented, that can acquire the data directly in compressed form by using special sensors. In this paper, the potential of CS for data compression of vibration data is investigated using simulation of the CS sensor algorithm. The acceleration data collected from the SHM system of Shandong Binzhou Yellow River Highway Bridge is used to analyse the data compression ability of CS. For comparison, the wavelet transform based and Huffman coding methods are also employed to compress the data. The results show that CS is useful for compression of vibration data in SHM of civil structures.

Abstract: Turbopump is a high-fault-rate component in Liquid Rocket Engine (LRE). The research on real-time process monitoring technology and system for turbopump is vital to increase the reliability and safety of LRE. In this paper, three real-time process monitoring algorithms for turbopump were studied firstly, on the basis of monitoring parameters selection and multiple domain feature extraction. Then, the real-time monitoring system realized by means of PXI (PCI eXtensions for Instrumentation) controller was introduced. And, aiming at the shortage of the previous system, the real-time process monitoring system based on DSP (Digital Signal Processor) for turbopump was studied to realize higher computing speed, which could conduce to extract multiple domain features and run manifold real-time monitoring algorithms. The new system could also satisfy the small-sized requirement in engine flying state.

Abstract: The paper explores the cyclo-stationary properties of vibration signals for estimation of gearbox condition. The advantage of such approach may be clearly seen especially for so called multi-faults problem, i.e. for more than one faults that occurred in the system. In complex mechanical systems like multistage gearboxes, such situation may be often seen. Although this approach becomes more and more popular, it has been noticed that there is difficult to find examples highlighting its potential, especially for real industrial situations. In order to fill partially the gap, the paper deals with the multi fault detection in complex mechanical systems like multi-stage gearboxes: fixed axis and planetary. It has been discussed that during the operation in such machines many faults may appear simultaneously and the classical method like envelope analysis is difficult to use. The paper presents the use of cyclo-stationary properties of signals to identify and characterize sources of modulation. From Spectral Correlation Density Map or more precisely Spectral Coherence Map have been observed the number of sources with different properties of modulation. It is shown that the number of harmonics is important for a kind of fault extraction and interpretation. This approach has been applied to two, three and five stage gearboxes used in mining industry. Vibration signals received in industrial environment during normal operation of objects are considered. It has been also proposed the simple diagnostic feature to estimate the changes of condition with application to a planetary stage in a 5-stage gearbox.