A review of major centrifugal pump failure modes with application to the water supply and sewerage industries

Centrifugal pumps are one of the world?s most widely used type of pump, having an extensiverange of applications, from food processing to water or sewage transportation. Problems that arisewithin these machines decrease the flow of the fluid within the pipelines, thus interrupting theproduction and transport of the fluid to its destination within the process. This may lead to other partsof the process system slowing down or behaving undesirably. As a result, it is imperative that thesepumps be correctly monitored, diagnosed, maintained or replaced prior to the pump failing catastrophically to reduce downtime, material cost, and labour costs. This paper reviews the major faultmodes that are found in centrifugal pumps, especially those in the water and sewage industry. Attentionis given to the nature of the faults, symptoms shown within the pump that could be utilised for specificfault detection and diagnosis, and any mechanical corrective procedures that exist to help alleviate theproblem. In addition, this paper contains a comparison and critique of previously published work thathas attempted to diagnose the fault modes of centrifugal pumps

Low cost remote data acquisition system

Remote data acquisition (RDAQ) is required in a number of vibration and noise measurement settings. Specialised systems exist for RDAQ, however they require significant investment to set up. This paper describes a low cost method of RDAQ which utilises a laptop computer, data acquisition system and a USB internet dongle. The system described in this paper would allow a professional vibration/noise measurement specialist to modify their existing data acquisition system for remote use with minimal cost. The system was tested both in an industrial and an academic setting for verification

A vibration cavitation sensitivity parameter based on spectral and statistical methods

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 bearing fault classifier using Artificial Neuro-Fuzzy Inference System (ANFIS) based on statistical parameters and Daubechies wavelet transform features

This paper presents an investigation process in building a bearing fault classifier based on wavelet coefficients and statistical parameter features. The building process starts by processing raw vibration data that was acquired from a bearing test rig. The data acquisition process was carried out for both normal (fault-free) and fault operation of a double row self-aligning ball bearing. Two accelerometers were used to collect the vibration data. One was attached near the bearing under investigation and the other was attached at one of the shaft support bearing of the test rig. The raw data was then processed to extract the statistical parameters (i.e., kurtosis, RMS, variance, standard deviation). Further, the same data was processed using a wavelet transform employing Daubechies wavelet filter to produce wavelet coefficients and their energy levels. The features generated from statistical parameters and wavelet transform scheme were then used to train an Artificial Neuro-Fuzzy Inference System (ANFIS). In order to reduce the number of rules generated during the training process, only two inputs were used for the purpose of building the classifier. The selection of the most influential inputs for the training process of the ANFIS is achieved through the use of the ANFIS built in capability of selecting the best correlation of two inputs towards one target output which best represents the bearing operating condition.The process of selecting the most influential inputs-output combination was carried out using an extensive computation to obtain the best related two inputs, out of the six inputs available. The number of input-output combinations tested was 720, equal to the total of six input permutations. In the search for the best combination of inputs-output, the possible application between the combination of statistical parameters, wavelet coefficients and wavelet’s level of energy were investigated extensively in order to obtain the best classifier for bearing fault diagnosis. The ANFIS was then implemented to capture the input-output relation of the selected inputs to generate a suitable classifier that could be used to classify bearing operating condition. The classifiers generated were then tested to evaluate their ability and accuracy in predicting faulty bearing operating conditions. The result showed that a bearing fault classifier produced by using ANFIS through the proposed combined features of statistical parameters and Daubechies wavelet transform is promising as a bearing fault classifier

Fundamental Issues in Self-Excited Chatter in Grinding

The modelling of chatter in grinding is more complex than for metal cutting. This is because the number of parameters that influence the onset of chatter in grinding is daunting. Also, unlike metal cutting, the growth of chatter in grinding may take a significant time and so growth rates are also important. Initially the modelling of grinding chatter was simply an extension of that already developed for metal cutting. However this was soon found to be inadequate and the models were increased in complexity to include improved grinding force models, the contact stiffness of the wheel and regeneration of surface waves on both the work and wheel. Some solutions to chatter in grinding were also proposed. Most notably these included the use of varying speed and flexible grinding wheels. This position paper re-visits the almost universal assumption that grinding chatter is always regenerative. It is shown that a grinding force model for oscillating conditions, that has been experimentally confirmed, indicates that both torsional vibration and non-regeneration need to be considered. The consequences for current methods of chatter elimination are discussed

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

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

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 vapour 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, 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

Modification of the ISO-10816 centrifugal pump vibration severity charts for use with octave band spectral measurements

The ISO standard 10816 gives acceptance levels of vibration for centrifugal pumps in the form of a severity Chart. The measured 10-1000 Hz RMS velocity vibration of pumps within a given size and physical setup can be judged against the severity chart limits to give an indication of the pumps running health. This single RMS velocity value, although having being shown to be a reasonably robust measurement tool for analysing the condition of a centrifugal pump, does not allow discrimination between failure types resulting in the increased vibration, and indeed overlooks the subtleties of the pump condition state. This limitation in the use of general RMS velocity vibration levels for use with rotating machinery health is well documented, and a vast number of more sophisticated techniques, to pin point faults in specific machinery, have been developed. These techniques, although powerful, often require detailed information, such as the number of balls in a specific bearing within the machine. This information is often not readily available for a given pump setup. Tailoring these sophisticated vibration diagnostic tools for a specific pump setup can require a considerable amount of man hours and expertise, therefore having general vibration diagnostic tools which don’t require extensive data about the particular pump setup would be ideal. It is proposed in this paper that the use of Octave band spectral measurements of pump vibration can strike a better balance between the two extremes of vibration analysis being: (i) overall RMS vibration velocity levels, (ii) highly specific analysis techniques such as envelope analysis for bearing fault detection.The use of Octave band spectral measurements still allows broad employment in centrifugal pump setups without a high degree of specific setup details being required. Within this paper modification of the ISO-10816 severity charts for use with Octave frequency band measurements is presented. With the use of some in-field vibration measurements, initial justification and validation of the modified vibration severity levels is presented

Measurement and modelling of noise-power-distance curves of a fixed-wing UAV

This paper presents an investigation into the noise produced by an unmanned aerial vehicle (UAV). The platform used, `Spotter', is a fixed-wing, light UAV comprising a 4-meter wingspan. Spotter was originally designed to perform long-endurance, all-weather patrol missions in coastal and maritime environments. This vehicle has been continuously upgraded and is now used in a broader range of applications. Increasing demand by research and industrial partners, as well as the UK Civil Certification Authority (CAA) has led to a survey of the Spotter's in-flight noise footprint. The CAA Operating Safety Case of this platform is currently being updated and the major findings are presented in the paper. Preliminary results were obtained in flight tests performed at the Draycot Aerodrome over two expeditions in the summer of 2021, in the UK. A series of flyovers, takeoff and landing operations were measured. Flyovers were performed at constant altitude at series of power settings, incrementing from low to maximum power output. These measurements are then used to generate Noise-Power-Distance curves for the Spotter UAV. Static directivity characteristics of the dual propeller setup were also measured, with intent of feeding into future airport exposure studies