A spokesperson for the Kogarah council said that the model is the first of its kind used to determine the condition of underground assets and will be able to predict the condition of the Kogarah Council’s 96 km of underground pipes with the reduced use of closed circuit television cameras (CCTV).
The Kogarah council said it was willing to use ‘fuzzy logic’ technology as most of its stormwater infrastructure dates back to 1938 and expensive ageing infrastructure replacement is a major issue due to the limited budget local governance bodies have for asset management. ‘Fuzzy logic’ offered a more cost effective method than CCTV surveys and inspections.
The ‘fuzzy logic’ model uses everyday language descriptors to mathematically predict the condition of the pipes, with output then compared to limited CCTV surveys for calibration.
The Kogarah council has a large database on CCTV inspections and have recently undertaken a survey of over 50 stormwater pipes of varied material, age, diameter and location within the drainage catchment as a sample dataset for calibrating the ‘fuzzy logic’ based model.
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A major difficulty concerning asset condition evaluation is that most of the knowledge acquired is approximate and cannot be translated into numbers required for assessment. ‘Fuzzy logic’ uses computer power and knowledge-based systems programming to quantify this knowledge for the decision making process.
The proposed assessment of Kogarah council’s stormwater drainage assets will be based on ‘distress factors’ or physical factors that contribute to the reduction in the drainage life cycle. For example, environmental factors, traffic loads, catchment land use, the physical condition of the pipe (i.e. age), and the current maintenance schedule.
The ‘Fuzzy logic’ system enables the use of engineering judgment, experience and scarce field data to translate the level of distress to condition ratings. The system is able to provide a more detailed rating system by assigning a level of confidence, such as ‘Good - confidence of 0.7,’ with the confidence level reflects how accurate the asset reading was. Rules can also be applied to the ‘Fuzzy logic’ system allowing the system to recognise that some objects may relate to one another and in this way it provides a more accurate reading.
The council said that readings from the ‘fuzzy logic’ system will be data-based in an Asset Condition Index. Each drainage asset will be tagged in this index under seven factors (excellent, good, adequate, fair, poor, bad, imminent failure) and this will be transferred to Stormwater Infrastructure Database.
Based on analysis detailed in a report by the Kogarah council, the ‘fuzzy logic’ asset management model will increase drainage serviceability levels by 20-30 per cent, as opposed to the standard model. The report says that given that the expected life of Kogarah council stormwater assets are in the range of 20-30 years, the use of the model will give the council an advantage in forecasting a higher written down value for its stormwater assets with less replacement in the short term. Also, the use of the model will provide a more level approach to asset replacement in the future.
The initial study shows close correlation between the predicted condition indicated by the model and actual CCTV survey footage of 50 stormwater pipes in the catchment.
The council has engaged, on a part-time basis, a PhD-qualified Modeller using the resources of UTS, including advanced technical software and journals to undertake the task. The two have successfully obtained a $A30,000 grant to further develop the model into a more-widely usable form. In the long term, this research will improve understanding, reduce costs, add to sustainability and increase efficiency.
The model is currently being refined and it is envisaged that it will be used to evaluate and prioritise condition of all stormwater drainage pipes within Kogarah without the need for any physical condition assessment.
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