John Machell

Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows

Water lost through leakage from water distribution networks is often appreciable. As pressure increases on water resources, there is a growing emphasis for water service providers to minimize this loss. The objective of the work presented in this paper was to assess the online application and resulting benefits of an artificial intelligence system for detection of leaks/bursts at district meter area (DMA) level. An artificial neural network model, a mixture density network, was trained using a continually updated historic database that constructed a probability density model of the future flow profile. A fuzzy inference system was used for classification; it compared latest observed flow values with predicted flows over time windows such that in the event of abnormal flow conditions alerts are generated. From the probability density functions of predicted flows, the fuzzy inference system provides confidence intervals associated with each detection, these confidence values provide useful information for f...

Long term variation in water colour from Yorkshire catchments.

Water colour is a problem in the upland water-gathering grounds of the UK. It has shown considerable variation over recent years and this needs to be put into the longer-term context. In order to do this, factors to convert water colour measured in absorbance units per metre (Au/m) to Hazen units are presented for ten sites in the Yorkshire region using data from August 1997 to June 1998. The conversion factors are site-specific and there is some evidence that they may show seasonal variation. There is also a short-term upward trend in the conversion factor for a number of catchments, which may be related to their recovery following the 1995 drought. Time series of water colour in Hazen from 1980 to 1998 are shown for selected sites. The seasonal variation in colour levels is disrupted at all sites during and following drought periods, notably 1990-1992 and 1995-1998 and, in the case of two sites with long-term colour measurements, the 1975-1976 drought. These periods are followed by enhanced levels of colour and, since the end of the 1995 drought, unprecedented high values have been recorded at some catchments.

Sensor-fusion of hydraulic data for burst detection and location in a treated water distribution system

Abstract This paper presents research into analysis and data fusion for sensors measuring hydraulic parameters (flow and pressure) of the pipeline water flow in treated water distribution systems. An artificial neural network (ANN) based system is used on time series data produced by sensors to construct an empirical model for the prediction and classification of leaks. A rules based system performs a fusion on the ANNs’ outputs to produce an overall state classification for a set of zones. Results are presented using data from an experimental site in a distribution system of a UK water company in which bursts were simulated by hydrant flushing. The ANN system successfully detected events and a study of the pressure gradient across the zone provided a more precise location within the zone.

Burst detection using hydraulic data from water distribution systems with artificial neural networks

This paper presents research into the application of artificial neural networks (ANNs) for analysis of data from sensors measuring hydraulic parameters (flow and pressure) of the water flow in treated water distribution systems. Two neural architectures (static and time delay) are applied for time series pattern classification from the perspective of detecting leakage. Results are presented using data from an experimental site in a distribution system of a UK water company in which bursts were simulated by hydrant flushing. Field trials have shown how ANNs can be used effectively for a leakage detection task. Both static and time delay ANNs learned patterns of leaks/bursts. The time delay neural network showed improved performance over the static network. It is concluded that the effectiveness of an ANN in discovering relationships within the data is dependent upon two key factors: availability of sufficient exemplars and data quality.

Bacterial water quality and network hydraulic characteristics: a field study of a small, looped water distribution system using culture-independent molecular methods

Aims:  To determine the spatial and temporal variability in the abundance, structure and composition of planktonic bacterial assemblages sampled from a small, looped water distribution system and to interpret results with respect to hydraulic conditions.

The water energy food nexus – challenges and emerging solutions

Water, energy and food are the pillars upon which society can further advance. The lack of a secure and economical provision of one of these essentials could result in a breakdown of supply, affordability and accessibility of the two others, especially for the most vulnerable in society. Management of the nexus is of great concern, and the Water Science Forum of the Royal Society of Chemistry have created this brief which outlines some of the challenges and emerging solutions that our members have been focused on.

Modeling and Field Work to Investigate the Relationship between Age and Quality of Tap Water

AbstractIt has been widely theorized that water age may be a useful indicator of the quality of water within drinking water distribution networks. However, there is limited evidence of model simulation results being related to empirical water quality (WQ) data to substantiate the theory. This paper presents the findings of investigations designed to determine if there was an observable relationship between mean water ages calculated using a WQ simulation model, and measured WQ in two live distribution networks. The age of water in all pipes was calculated using Aquis hydraulic and WQ modeling software. Historic regulatory WQ data was examined to determine if there was a relationship between general WQ and calculated water age within the networks. A more detailed study was then undertaken in one network by translating model locations that were representative of the spread of water age into real-world locations. WQ samples were taken intensively from these sites and analyzed for a range of aesthetic, physic...

ONLINE APPLICATION OF ANN AND FUZZY LOGIC SYSTEM FOR BURST DETECTION

Minimising the loss of treated water from water supply systems due to burst and leakage is an ongoing issue for water service providers around the world. Flow monitoring techniques are currently used by the water industry to monitor leakage, generally offline through the application of mass balance type calculations or through observations of change in night line values. The data for such analysis has, until recently, been at best collected 24 hourly via SMS technology. The objective of the study reported here was to assess the online application of an AI system to a real distribution system and the potential benefits of so doing. Specifically the application of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FIS), which are computational techniques in the field of Artificial Intelligence (AI). The online hybrid ANN/FIS system developed uniquely uses DMA (District Meter Areas) level flow data for the detection of leaks/bursts as they occur. The ANN model (a Mixture Density Network) was trained using a continually updated historic database that constructed a probability density model of the future flow profile. A FIS, used for classification, compared observed flows with the probability density function of predicted flows over time windows such that confidence intervals could be assigned to alerts and further, an accurate estimate of likely burst size provided. A Water Supply System in the UK was used for the case study. The case study pilot area has near real-time flow data provided by General Packet Radio Service (GPRS). The online AI leak/burst detection system was constructed to operate along side an existing flat line alarm system, and continuously analyse every twelve hours a set of 50 DMAs of various size, complexity and connectivity within the case study area. Results are presented from a six month period. The new system identified a number of events and alerts were raised prior to their notification in the control room; either through flat line alarms or customer contacts. Examples are given of their correlation with burst reports and subsequent mains repairs. 56% of AI alerts were found to correspond to bursts confirmed by repair data or customer contacts reporting bursts. The study shows that the integration of the AI system with near real time communications can facilitate rapid determination (i.e. before customers are impact) of abnormal flow patterns. It is concluded from the study that the system is an effective and viable tool for online burst detection in water distribution systems.

Field Studies and Modeling Exploring Mean and Maximum Water Age Association to Water Quality in a Drinking Water Distribution Network

AbstractThis paper presents the findings of an investigation into predicted/modeled water age and the associated quality characteristics within a UK drinking water distribution network to determine if there is a discernable link. The hydraulic and water quality software Aquis was used to identify water volumes of different ages, generated by localized demand patterns in pipes that are in close proximity to one another. The pipe network studied was small spatially, of a single material, and had a consistent demand attributable to serving predominately light industry, but with interesting hydraulic patterns involving loops and mixing of water volumes, and some long retention times. Field work was undertaken to obtain water quality samples from five network locations identified as containing a broad range of calculated water age. The samples were analyzed for standard regulated parameters by a UK Accreditation Service (UKAS) [formerly known as the National Measurement Accreditation Service (NAMAS)] accredite...

Drinking water purity – a UK perspective

Water purity is a vague term. Applied to drinking water, the emphasis of pure can mean ‘free from all types of bacteria and viruses’ as defined by the United States Environmental Protection Agency, or as being ‘wholesome’ when defined within Great Britain. US and British standards are based on the protection of public health. Strictly enforced values for a broad set of physical, chemical and biological parameters, informed by expert evidence gathered from many countries over a long period of time, are applied in an effort to ensure a minimum purity is achieved regardless of geographical location within those areas. Other countries like Australia, Canada and New Zealand however, do not have such strict legal definitions. Instead, best endeavours under local circumstances, measured against ‘guideline’ values for a narrow set of parameters, are used to judge water quality, and hence purity. These discrepant definitions can lead to confusion so this brief has been created to clarify current understanding of the meaning of ‘water purity’.