Abstract
In order to develop an automatic control system for public sewage treatment facilities, it is necessary to conduct a technical analysis of each water quality measurement item to discover new trends or patterns. In this study, a failure prediction algorithm for each instrument or unit process was developed for the automatic control of public sewage treatment facilities, with the optimal data sampling method and abnormality detection criteria for each water quality item. In order to establish the confidence intervals for the five telemonitoring systems (TMS) parameters (chemical oxygen demand, suspended solids, total nitrogen, total phosphorus, and pH) in the sedimentation tank and bioreactor, that during a set period, 48, 72, or 168 samples were taken and the error rate was reviewed. Based on this, 48 samples were established as the optimal level with an error rate of 1.46%. In addition, the abnormality rate for the TMS data at a confidence interval of μ±3σ averaged 1.73%, confirming that any abnormalities that were recorded were not solely the result of simple data errors but also included genuine problems with an instrument or unit process.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
