The ever increasing size of wind turbines and the move to build them offshore have accelerated the need for optimised maintenance strategies in order to reduce operating costs. Predictive maintenance ...requires detailed information on the condition of turbines. Due to the high costs of dedicated condition monitoring systems based on mainly vibration measurements, the use of data from the turbine supervisory control and data acquisition (SCADA) system is appealing. This review discusses recent research using SCADA data for failure detection and condition monitoring (CM), focussing on approaches which have already proved their ability to detect anomalies in data from real turbines. Approaches are categorised as (i) trending, (ii) clustering, (iii) normal behaviour modelling, (iv) damage modelling and (v) assessment of alarms and expert systems. Potential for future research on the use of SCADA data for advanced turbine CM is discussed.
Information about vibrating objects can be obtained by vibration measurements. Piezoelectric sensors made by piezoelectric ceramics, quartz, or organic piezoelectric materials, e. g. polyvinylidene ...fluoride (PVDF) have been adopted by many researchers to measure vibrations. Among these piezoelectric materials, PVDF has attracted much attention for its excellent properties such as outstanding chemical resistance, high thermal stability, low permitivities, low acoustic impedances, flexibility and membrane forming properties. In this paper, PVDF is introduced in brief. In addition, this paper briefly reviews the use of PVDF films as sensors for vibration measurement in the areas of portable medical detections, structural health monitoring, mechanical equipment vibration measurements and other applications. Meanwhile, some cases which have good low-frequency performances or novel features in structures will be especially introduced to provide helpful experiences for future applications. In the end, a spiral-shaped PVDF cantilever and a double-clamped PVDF beam of two piezoelectric energy harvesters are mentioned to provide ideas for reducing the resonant frequencies and enhancing the output signals of PVDF vibration sensors respectively. The idea of how to enhance the output signals of PVDF sensors for low frequency vibration measurements may be helpful to the development of geophone.
Transit-oriented development, such as metro depot and over-track building complexes, has expanded rapidly over the last 5years in China. Over-track building construction has the advantage of ...comprehensive utilization of land resources, ease of commuting to work, and provide funds for subway construction. But the high frequency of subway operations into and out of the depots can generate excessive vibrations that transmit into the over track buildings, radiate noise within the buildings, hamper the operation of vibration sensitive equipment, and adversely affect the living quality of the building occupants. Field measurements of vibration during subway operations were conducted at Shenzhen, China, a city of 10.62 million people in southern China. Considering the metro depot train testing line and throat area train lines were the main vibration sources, vibration data were captured in five measurement setups. The train-induced vibrations were obtained and compared with limitation of FTA criteria. The structure-radiated noise was calculated using measured vibration levels. The vertical vibration energy directly passed through the columns on both sides of track into the platform, amplifying vibration on the platform by up to 6dB greater than ground levels at testing line area. Vibration amplification around the natural frequency in the vertical direction of over-track building made the peak values of indoor floor vibration about 16dB greater than outdoor platform vibration. We recommend to carefully examining design of new over-track buildings within 40m on the platform over the throat area to avoid excessive vertical vibrations and noise. For both buildings, the measured vertical vibrations were less than the FTA limit. However, it is demonstrated that the traffic-induced high-frequency noise has the potential to annoy occupants on the upper floors.
•Train-induced vibrations in the metro depot and over-track buildings were measured and studied.•Building train-induced vibrations were amplified around the vertical natural frequency.•Building train-induced vibrations over throat area can potentially exceed the FTA limits within 40m.•Traffic-induced high-frequency noise has the potential to annoy occupants on upper floors.
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Condition monitoring (CM) of mechanical systems such as gear transmissions can be performed with vibration measurements and processing of the recorded signals for identification of possible faults. ...The accuracy and robustness of a CM application depends among others on the availability of data for different health states which typically requires complete experimental measurements. The presented work contains a novel CM scheme using a Convolutional Neural Network (CNN) trained by data generated through numerical simulations of a Multibody Dynamics (MBD) system. The goal is to perform damage identification on different health states by exploiting simulated instead or experimental responses for supervised health state classification. First, a MBD model corresponding to the real system is developed and optimized using experimental measurements of the healthy mechanical structure. Then, data is generated by the MBD model using an uncertainty simulation repetitive load case algorithm to account for various model parameters inaccuracies. The simulated data is used after to train a supervised CNN classifier which is finally validated on vibration measurements of the physical system. The classifier is shown to be capable of generalizing to the experimental damages, proving therefore the potential of the model-based proposed framework for CM. The presented methodology may find application in cases where experimental measurements are difficult or nearly impossible to acquire. CM was performed on the benchmark gear transmission systems for different rotation speeds and the limitations are discussed.
•Supervised training of Machine Learning classifiers by numerically generated responses.•Damage detection and SHM systems with Finite Element models.•Model error perceived by the trained ANN, ...depending on the damage identification scenario.•Reliability testing of numerical data.•Experimental validation on a lab-scale bridge truss.
Progress in the field of Structural Health Monitoring (SHM) includes applications of model data approaches with numerically generated responses originating from Finite Element (FE) simulations. The simulated data may be used for supervised training of Machine Learning classifiers to perform damage identification on some later experimental state. The reliability of the numerically trained classifiers depends on the quality of the training data in terms of the simulation model error contained. Even though FE models can be updated on the intact state for better accordance with the experiment, some model error still remains for most complex structures. This error can limit the ability of generalization to the unmeasured yet damaged experimental states depending on how distinct they are. In the present work, the effect of model error on subsequent classification of experimental damaged states is tested for a lab-scale bridge truss. A Convolutional Neural Network classifier is applied, trained by FE responses. Results show that larger and more distinct damages can be classified with more accuracy compared to small and less distinct, with the latter showing higher prediction bias. The numerical data reliability is found to be reflected on the intact state numerical and experimental feature map shifts.
•Phase analysis of ground vibrations due to a leak from a buried water pipe.•Underlying physics determined from spatially unwrapped phase data.•Analytical model, numerical simulations (FEM) and ...experimental data are presented.
One way to locate a buried plastic water pipe is to measure the surface vibration due to a leak in the region above the pipe, and to process the data to infer the pipe location. This paper investigates the physical mechanisms that propagate leak noise through the pipe and the surrounding soil to the ground surface. An analysis is carried out of the relative phase between vertical ground vibration measurements at points in a grid above the pipe. The study involves experimental measurements from a site in the UK with a more realistic leak mechanism compared to recent research, a simplified analytical model to gain insight into the underlying physics, and a numerical model to validate some of the assumptions made in the derivation of the analytical model. Three waves are principally involved in propagating leak noise to the ground surface from the pipe, namely the predominantly fluid-borne wave in the pipe, and the shear and compressional waves in the soil radiating from the pipe. Their influence on the ground surface vibration is investigated through measured and simulated phase contours over a rectangular grid of surface velocity measurements. It is shown how shear and compressional waves combine to affect the shape of the lines of constant phase on the ground. The results demonstrate the potential of the proposed analytical and numerical models to investigate wave radiation from buried water pipes, and possible pipe location strategies using phase data from surface vibration measurements.
The detection of cavitation formation in hydraulic turbomachinery has been widely investigated due to its significant impact on their steady and dynamic operation. The aim of this study is the ...application of Spectral Kurtosis tool in order to effectively detect the impulsive shock waves generated during the implosion of vapour bubbles. The methodology is applied and evaluated on the vibration signals obtained from two different semi-open impellers. The results under initial cavitating conditions show that the high frequency implosions of vapour bubbles interact with the low frequency passing of the rotating blades and compose part of the vibration signal. The application of the band pass filter, with central frequency and bandwidth estimated from the Fast Kurtogram, to the original signal allows to extract this information both in time and in frequency domain, and to correlate the periodic impulsive behaviour with the blade passing frequency of the impeller. The present results support the establishment of a robust detection cavitation criterion in centrifugal pumps and show that Spectral Kurtosis is a useful tool for the prevention of related faults in centrifugal pumps.
The continuously increasing industrial productivity has resulted in a great breakthrough in the field of maintenance on centrifugal pumps in order to ensure their optimum operation under different ...operating conditions. One of the important mechanisms that affect the steady and dynamic operation of a pump is cavitation, which appears in the low static pressure zone formed at the impeller entrance region. This paper investigates the inception and development of cavitation in three different impellers of a laboratory centrifugal pump with a Plexiglas casing, using flow visualization, vibration and acoustic emission measurements. The aim of this study is the development of an experimental tool that detects cavitation in different impellers and the further understanding of the effects of blade geometry in cavitation development. The results show that the geometrical characteristics of the impeller affect cavitation development and behavior, while an acoustic emission sensor and an accelerometer can be applied for successfully detecting the onset of this mechanism.
Full-field measurements of structural vibrations have been achieved by incoherent optical methods with video cameras such as digital image correlation and optical flow. In contrast to coherent ...optical methods such as scanning laser vibrometers, incoherent optical methods are low-cost and easy to set up. However, the sensitivity (minimum measurable displacement) of incoherent optical methods is generally lower than that of coherent optical methods. Typically, the sensitivity of incoherent optical methods is essentially limited by the finite bit depth of the digital camera due to the quantization with round-off errors. Quantitatively, this theoretical sensitivity limit is determined by the bit depth B as δp=1/(2B−1) pixel which corresponds to a displacement causing an intensity change of one gray level. Fortunately, natural dithering may be leveraged to overcome the quantization and exceed the sensitivity limit, achieving super-sensitivity.
In this work, we first study the mechanism of the sensitivity limit induced by the quantization and the critical limitation of existing super-sensitivity methods in the full-field measurement of structural vibration. Addressing such a limitation, we present a general adaptive weighted averaging method with dithering, achieving super-sensitivity incoherent optical measurement of full-field deformational vibration of flexible structures. Specifically, both spatial and temporal samplings of the pixels are leveraged simultaneously to adaptively identify the motion (deformation) shape of the structure by principal component analysis (PCA) of spatiotemporal pixel intensities. Then, the identified deformation shape is used to perform a deformation-shape-weighted averaging over spatial pixels with dithering, revealing the sub-sensitivity displacement while retaining spatial resolution at full field. Numerical simulations and laboratory experiments are performed for principle explanation and method validation. Particularly, we derive a mathematical model of the minimum measurable vibration amplitude A∗ for the developed super-sensitivity method, which is found to be determined by the number of spatial pixels for averaging Ns and the noise level σn in the imaging system. Thus, this work provides, for the first time, a rigorous quantification of the sensitivity of incoherent optical measurement for structural vibration, and a new quantitative method to achieve super-sensitivity full-field measurement of structural vibration.
•The sensitivity of incoherent optical measurement is limited by the finite bit depth.•A super-sensitivity full-field structural vibration measurement method is proposed•Numerical simulations and laboratory experiments are conducted for method validation.•The model of the minimum measurable vibration amplitude is obtained.
Hot metal desulfurization is the main process step for removing sulfur in blast furnace‐based steelmaking. A desulfurization reagent is pneumatically injected into the hot metal through a submerged ...lance causing it to vibrate. The aim of this study is to develop a mechanical vibration measurement‐based method that can detect changes in the gas‐forming properties of the reagent. The detection is performed using Elastic Net regression and eXtreme Gradient Boosting‐based classification models the classification performance of which is compared. The lance aging causes changes in its dynamic characteristics, and the disturbing effect of this is removed from the measured data of the lance vibration prior to classification by means of a developed cleaning algorithm. The best classification performance in detecting changes in the gas‐forming properties, with an area under the receiver operating characteristic curve of 0.916 and Matthews correlation coefficient of 0.699, is achieved using an Elastic Net regression‐based classification model. The results of this work serve as a basis for developing industrial applications in which the effective utilization of the excitation, such as vibrations generated by the gas formation can be utilized for process monitoring and as a soft sensor for predicting the reagent‐induced process variance.
Hot metal desulfurization is the main process step for removing sulfur in blast‐furnace steelmaking. Herein, vibration measurement is coupled with machine learning methods to detect differences in reagent properties.
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