Cavitation is one of the main problems reducing the longevity of centrifugal pumps in industry today. If the pump operation is unable to maintain operating conditions around the best efficiency point, it can be subject to conditions that may lead to vaporisation or flashing in the pipes upstream of the pump. The implosion of these vapour bubbles in the impeller or volute causes damaging effects to the pump. A new method of vibration cavitation detection is proposed in this paper, based on adaptive octave band analysis, principal component analysis and statistical metrics. Full scale industrial pump efficiency testing data was used to determine the initial cavitation parameters for the analysis. The method was then tested using vibration measured from a number of industry pumps used in the water industry. Results were compared to knowledge known about the state of the pump, and the classification of the pump according to ISO 10816.

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The sun-planet and ring-planet tooth mesh stiffness variations and the resulting transmission errors are the main internal vibration generation mechanisms for planetary gear systems. This paper presents the results of torsional stiffness analysis of involute spur planetary gear systems in mesh using finite element methods. A planetary gear model with three planet gears and fixed ring gear and its subsystem models have been developed to study the subsystem and overall torsional stiffnesses. Based on the analysis of torsional mesh stiffness, predictive models for single branch sun-planet-ring and overall planetary gear torsional stiffnesses have been proposed. A crack coefficient was introduced to the sun-planet and ring-planet meshes to predict the effect and sensitivity of changes to the overall torsional mesh stiffness. The resulting mesh stiffness crack sensitivity of the overall gear system was analysed under quasi-static conditions. It was found that the carrier arm stiffness has great influence on the crack sensitivity while the overall stiffness was most sensitive to the crack on the sun-planet mesh.

Past researchers suggested that "static instabilities" exist at certain rotational speeds of whirling rods. This paper shows these instabilities are an artefact of the material constitutive laws that are being used well outside their range of applicability. An alternative approach is developed where strains due to rotation are separated from the superimposed vibration. This enables the generally predicted lowering of longitudinal natural frequencies with rotational speed shown to be simply a result of the bulk changes in the geometry of whirling rods. Steady-state equations of whirling rods are formulated in Lagrangian coordinates. Due to the nonlinear nature of the governing equations, an original numerical method is applied to solve the problem. Numerical results are compared with analytical results obtained from the linearized uniaxial model. There is close agreement between these two models at low angular velocities. However, at high angular velocities, discrepancies between them arise, confirming that the nonlinear strain-displacement relationship has significant effect on the results and the inferred "static instabilities." This approach first solves the "static" problem of the deformed geometry of a highly strained whirling rod before longitudinal natural modes are determined by classical methods. Furthermore, conditions for existence and uniqueness of solutions are derived.

In this paper, the features of vibration signals from normal and faulty conditions of a centrifugal pump were extracted from time-domain data using the discrete wavelet transform (DWT). The DWT with Multi Resolution Analysis (MRA) was used to pre-process raw vibration signals prior to extraction of statistical features. The features obtained were used as input to Principal Component Analysis (PCA). A method based on PCA was then developed to build a framework for multi-fault diagnosis of centrifugal pumps by using historical normal conditions. The fault detection was determined using T 2 -statistics and Q-statistics while fault identification was carried out through the combination of loadings and scores of principal components (PCs). The normal and faulty conditions of the centrifugal pump were collected from the Spectra Quest Machinery Fault Simulator. Various fault conditions were investigated in the experiment including cavitation, impeller fault, and combination of impeller fault and cavitation. The results showed that combined wavelet-PCA can be used to detect multi-faults in the centrifugal pump. Furthermore, the combination of loadings and scores of PCs was demonstrated which showed effective fault identification.