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首页> 外文期刊>IEEE sensors journal >Robust Sensor Suite Combined With Predictive Analytics Enabled Anomaly Detection Model for Smart Monitoring of Concrete Sewer Pipe Surface Moisture Conditions
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Robust Sensor Suite Combined With Predictive Analytics Enabled Anomaly Detection Model for Smart Monitoring of Concrete Sewer Pipe Surface Moisture Conditions

机译：强大的传感器套件结合预测分析，使混凝土管道表面湿度条件的智能监控异常检测模型

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摘要

Globally, the water industry considers microbial induced corrosion of concrete sewer pipes as a serious problem. There are reported analytical models and data analytic models that are used to predict the rate of corrosion throughout the sewer network. Those models incorporate surface moisture conditions of concrete sewer pipes as observations. Due to the unavailability of sensors to monitor concrete sewer surface moisture conditions, water utilities use surrogate measures such as relative humidity of the air as an observation for the model. Hence, the corrosion predictions are often hampered and associated with prediction uncertainties. In this context, this paper presents the development and successful evaluation of an electrical resistivity based sensor suite for estimating the surface moisture conditions of concrete sewer pipes. The sensor was deployed inside a municipal sewer pipe of Sydney city, Australia to carry out field measurements. The post-deployment study revealed the survival of the sensing system under hostile sewer conditions and demonstrated their suitability for long-term monitoring inside sewer pipes. Besides sensor development, a predictive analytics model was proposed for anomaly detection. The model incorporates a forecasting approach using a seasonal autoregressive integrated moving average technique for anomaly detection. The model was evaluated using the sensor data and results demonstrated its effective performance. Overall, the proposed sensor suite can ameliorate the way water utilities monitor sewer pipe corrosion.
机译：在全球范围内，水业认为微生物诱导的混凝土下水道管道腐蚀是一个严重的问题。有报告的分析模型和数据分析模型用于预测整个下水道网络的腐蚀速率。这些模型将混凝土下水道管道的表面湿气条件纳入观察结果。由于传感器的不可用来监测混凝土下水道表面的水分条件，水实用程序使用替代措施，例如空气的相对湿度作为模型的观察。因此，腐蚀预测通常被阻碍并与预测不确定性相关联。在这种情况下，本文介绍了基于电阻率的传感器套件的开发和成功评价，用于估算混凝土下水道管道的表面湿度条件。该传感器部署在澳大利亚悉尼市的市政下水道管内，开展现场测量。后部署后研究显示了敌对下水道条件下的传感系统的生存，并证明了它们在下水道管内的长期监测的适用性。除传感器开发外，提出了一种用于异常检测的预测分析模型。该模型采用了一种预测方法，用于使用季节性自回归综合移动平均技术进行异常检测。使用传感器数据进行评估模型，结果表明其有效性。总的来说，所提出的传感器套件可以改善水公用事业监控下水道管道的方式。

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