An exact series solution for the vibration analysis of cylindrical shells with arbitrary boundary conditions

In this paper, an exact series solution for the vibration analysis of circular cylindrical shells with arbitrary boundary conditions is obtained, using the elastic equations based on Flügge's theory. Each of the three displacements is represented by a Fourier series and auxiliary functions and sought in a strong form by letting the solution exactly satisfy both the governing differential equations and the boundary conditions on a point-wise basis. Since the series solution has to be truncated for numerical implementation, the term exactly satisfying should be understood as a satisfaction with arbitrary precision. One of the important advantages of this approach is that it can be universally applied to shells with a variety of different boundary conditions, without the need of making any corresponding modifications to the solution algorithms and implementation procedures as typically required in other techniques. Furthermore, the current method can be easily used to deal with more complicated boundary conditions such as point supports, partial supports, and non-uniform elastic restraints. Numerical examples are presented regarding the modal parameters of shells with various boundary conditions. The capacity and reliability of this solution method are demonstrated through these examples. © 2012 Elsevier Ltd. All rights reserved.

Comparison of different analysis techniques for the determination of muscle onset in individuals with patellofemoral pain syndrome

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Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Joint Vibration Analysis in Patients with Articular Inflammation

The study of articular sounds using a computerized system (SonoPAK) in patients with temporomandibular disorders (TMD) of inflammatory origin revealed an increase of vibratory energy when compared to asymptomatic individuals. The following conclusions were reached: 1. The amount of vibratory energy registered in these patients ranged from 8.50 to 57.61 Hz. The major vibrations occurred in the middle of the mandibular opening cycle; 2. The mean vibratory energy measured at less than 300 Hz was between 5.70 and 48.64 Hz and at higher than 300 Hz was between 3.70 and 8.99 Hz; 3. The peak amplitude in the patients with inflammation ranged from 0.35 to 3.96 Pascal and the peak of frequency from 83.20 to 120.20 Hz.

Design of a labVIEW system applied to predictive maintenance

The implementation of vibration analysis techniques based on virtual instrumentation has spread increasingly in the academic and industrial branch, since the use of any software for this type of analysis brings good results at low cost. Among the existing software for programming and creation of virtual instruments, the LabVIEW was chosen for this project. This software has good interface with the method of graphical programming. In this project, it was developed a system of rotating machine condition monitoring. This monitoring system is applied in a test stand, simulating large scale applications, such as in hydroelectric, nuclear and oil exploration companies. It was initially used a test stand, where an instrumentation for data acquisition was inserted, composed of accelerometers and inductive proximity sensors. The data collection system was structured on the basis of an NI 6008 A/D converter of National Instruments. An electronic circuit command was developed through the A/D converter for a remote firing of the test stand. The equipment monitoring is performed through the data collected from the sensors. The vibration signals collected by accelerometers are processed in the time domain and frequency. Also, proximity probes were used for the axis orbit evaluation and an inductive sensor for the rotation and trigger measurement. © (2013) Trans Tech Publications, Switzerland.

Maintenance of a reducer by vibration and wear particles analysis

Purpose - The purpose of the paper is to provide information on wear debris on oil and vibration analysis as predictive maintenance techniques in reducer. Design/methodology/approach - The estate of a reducer is verified by analyzing the vibration and oil conditions of a test rig under well-designed conditions utilizing some predictive variables. Findings - According to the vibration and oil analysis it is found out what it was happening into the reducer without disassembling it. Practical implications - This paper demonstrates the use of oil debris analysis and vibration analysis as a technique that enhances preventive maintenance practices. The paper helps practitioners to utilize these techniques more effectively. Originality/value - This paper gives information about two predictive maintenance techniques with a test rig. © Emerald Group Publishing Limited.

Vibration and wear particles analysis in a test stand

Purpose - This paper aims to provide information on wear debris on oil and vibration analysis as predictive maintenance techniques. Design/methodology/ approach - The estate of a reducer is verified by analyzing the vibration and oil conditions of a test rig under some variables. Findings - According to the vibration and oil analysis it was found what was happening in the reducer without disassembling it. Originality/value - This paper gives information about two predictive maintenance techniques with a test rig. © Emerald Group Publishing Limited.

Vibration and oil analysis for monitoring problems related to water contamination in rolling

Trying to reduce particle contamination in lubrication systems, industries of the whole world spend millions of dollars each year on the improvement of filtration technology. In this context, by controlling fluid cleanliness, some companies are able to reduce failures rates up to 85 percent. However, in some industries and environments, water is a contaminant more frequently encountered than solid particles, and it is often seen as the primary cause of component failure. Only one percent of water in oil is enough to reduce life expectancy of a journal bearing by 80 percent. For rolling bearing elements, the situation is worse because water destroys the oil film and, under the extreme temperatures and pressures generated in the load zone of a rolling bearing element, free and emulsified water can result in instantaneous flash-vaporization giving origin to erosive wear. This work studies the effect of water as lubricant contaminant in ball bearings, which simulates a situation that could actually occur in real systems. In a designed bench test, three basic lubricants of different viscosities were contaminated with different contents of water. The results regarding oil and vibration analysis are presented for different bearing speeds.

Compositional analysis for an unbiased measure of soil aggregation

Soil aggregation is an index of soil structure measured by mean weight diameter (MWD) or scaling factors often interpreted as fragmentation fractal dimensions (D-f). However, the MWD provides a biased estimate of soil aggregation due to spurious correlations among aggregate-size fractions and scale-dependency. The scale-invariant D-f is based on weak assumptions to allow particle counts and sensitive to the selection of the fractal domain, and may frequently exceed a value of 3, implying that D-f is a biased estimate of aggregation. Aggregation indices based on mass may be computed without bias using compositional analysis techniques. Our objective was to elaborate compositional indices of soil aggregation and to compare them to MWD and D-f using a published dataset describing the effect of 7 cropping systems on aggregation. Six aggregate-size fractions were arranged into a sequence of D-1 balances of building blocks that portray the process of soil aggregation. Isometric log-ratios (ilrs) are scale-invariant and orthogonal log contrasts or balances that possess the Euclidean geometry necessary to compute a distance between any two aggregation states, known as the Aitchison distance (A(x,y)). Close correlations (r>0.98) were observed between MWD, D-f, and the ilr when contrasting large and small aggregate sizes. Several unbiased embedded ilrs can characterize the heterogeneous nature of soil aggregates and be related to soil properties or functions. Soil bulk density and penetrater resistance were closely related to A(x,y) with reference to bare fallow. The A(x,y) is easy to implement as unbiased index of soil aggregation using standard sieving methods and may allow comparisons between studies. (C) 2012 Elsevier B.V. All rights reserved.

Application of rotor response analysis to fault detection in hydro powerplants.

In this article some considerations obtained during the utilization of rotor response analysis techniques in hydraulic powerplants are discussed. An applied research work was carried out in two hydraulic turbines analysing the rotor response both theoretically and experimentally. A developed mathematical model was used to simulate the rotordynamic behaviour of Francis and Kaplan turbines. The main dynamical effects that appear during the operation of the machines are discussed too. A series of measurements were carried out in the turbines using impact hammers to determine the modal behaviour of the units. The tests were carried out with the machine still and in operation. Some results and the comparison with the theory is presented in this article. The improved theoretical model was used for a sensitivity analysis of the different bearings to the main excitations that fake place during the machine operation. From this analysis, the best measuring points for condition monitoring were determined.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

A model for computing vibration induced stresses of electronic components in a general flexible mounting

This paper develops a novel full analytic model for vibration analysis of solid-state electronic components. The model is just as accurate as finite element models and numerically light enough to permit for quick design trade-offs and statistical analysis. The paper shows the development of the model, comparison to finite elements and an application to a common engineering problem. A gull-wing flat pack component was selected as the benchmark test case, although the presented methodology is applicable to a wide range of component packages. Results showed very good agreement between the presented method and finite elements and demonstrated the usefulness of the method in how to use standard test data for a general application. © 2013 Elsevier Ltd.

Procedimentos de coletas de óleo para análise preditiva de turbinas à gás

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Manutenção de redutores de velocidade pela integração das técnicas preditivas de análise de vibrações e análise de óleo lubrificante

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