Rodney Entwistle

A vibration cavitation sensitivity parameter based on spectral and statistical methods

Octave band analysis and PCA used on RMS velocity to obtain key indicators.Mahalanobis distance is used to set thresholds since data is normally distributed.Pump health separated into no cavitation, incipient, and fully formed condition.Method works on a range of types and sizes of centrifugal pumps. 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.

A Review of Machinery Diagnostics and Prognostics Implemented on a Centrifugal Pump

Centrifugal pumps are a widely used machine found in industries such as water, sewerage, oil, and gas. As a result, it is vital that these pumps are monitored, diagnosed, maintained, or replaced prior to the pump failing to reduce downtime, material, and labour costs. Most companies employ a run-to-fail method or a time-based maintenance strategy to service their pumps, instead of condition based maintenance or a predictive maintenance strategy. This paper reviews the state of art in diagnostics and prognostics pertaining to centrifugal pumps. Attention is given to detailing the methods of application, detection of fault modes and results used by researchers in the main areas of diagnostics and prognostics.

A single cavitation indicator based on statistical parameters for a centrifugal pump

Cavitation is one of the major problems associated with the operation of centrifugal pumps. Cavitation occurs when vapor bubbles that are formed due to a drop in pressure in the pipes upstream of the centrifugal pump implode under the added pressure within the volute of the pump. These implosions wear away the impeller, and sometimes the volute itself, which if left unchecked, would render the pump inoperable. Much research has been done in the detection of cavitation through: indicators in certain audible frequencies, drop in the net positive suction head (NPSHa), visual inspection using a transparent casing and a stroboscopic light, paint erosion inside the volute, and on the impeller, changes in pressure within the flow or volute, and vibration within certain frequency ranges. Vibration detection is deemed as one of the more difficult methods due to other structural and environmental factors that may influence which frequencies may be present during the onset of cavitation. Vibration measurement, however, is most easily measured and deployable in an automated condition monitoring scenario. It is proposed that an increasing trend in a set of statistical parameters, rather than a firm threshold of a single parameter, would provide a robust indication for the onset of cavitation. Trends in these statistical parameters were obtained from data collected on a pump forced to cavitate under several different operating conditions. A single cavitation indicator is outlined utilizing these statistical parameters that can quantify the level of cavitation in a centrifugal pump.

Multi Fault Diagnosis of the Centrifugal Pump Using the Wavelet Transform and Principal Component Analysis

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.

Cavitation Sensitivity Parameter Analysis for Centrifugal Pumps Based on Spectral Methods

Cavitation is a major problem facing centrifugal pumps in industry today. Unable to constantly maintain operating conditions around the best efficiency point, centrifugal pumps are 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 cavitation detection is proposed in this paper based on spectral methods. Data used to determine parameters were obtained under ideal conditions, while the method was tested using industry acquired data. Results were compared to knowledge known about the state of the pump, and the classification of the pump according to ISO 10816.

The Torsional Stiffness of Involute Spur Planetary Gears

This paper presents the results of torsional stiffness analysis of involute spur planetary gears in mesh using finite element methods. A planetary gear model with 3 planet gears and its subsystem models have been developed to study the relationship between the overall torsional stiffness and the subsystem torsional stiffness. The subsystem models include one isolated sun-planet-ring pair, one isolated sun-planet external pair and one isolated planet-ring internal pair. A strategy utilising a small preload step via a weak spring was first applied to eliminate the gap between the teeth and then different torque levels were applied to calculate the transmission error due to the resulting elastic deformations. This calculation was repeated at multiple positions covering two tooth mesh cycles in the overall and subsystem models. The theoretical gear contact position was determined using an ANSYS APDL program and the gear rolling range was digitized into equidistant rolling angles. The sun-planet torsional stiffness variation has been shown to dominate the combined torsional stiffness and, based on the subsystem torsional stiffness, an analytical method for predicting the overall torsional stiffness is presented.